Youth Involvement in the Sex Trade - A National Study, Swaner et al, 2016.pdf

• Aug. 12, 2016 • Topics: Sexual Assault, Crime/Demographics, Victims, Statistics/Trends, Juveniles, Failure to Protect (Juveniles)

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The author(s) shown below used Federal funds provided by the U.S.
Department of Justice and prepared the following final report:

Document Title:

Youth Involvement in the Sex Trade: A National
Study

Author(s):

Rachel Swaner, Melissa Labriola, Michael
Rempel, Allyson Walker, Joseph Spadafore

Document No.:

249952

Date Received:

June 2016

Award Number:

2009-MC-CX-0001

This report has not been published by the U.S. Department of Justice.
To provide better customer service, NCJRS has made this federally
funded grant report available electronically.

Opinions or points of view expressed are those
of the author(s) and do not necessarily reflect
the official position or policies of the U.S.
Department of Justice.

Youth
Involvement in
the Sex Trade
A National Study
By Rachel Swaner, Melissa Labriola, Michael Rempel, Allyson Walker, and
Joseph Spadafore

520 Eighth Avenue, 18 th Floor
New York, New York 10018
646.386.3100 fax 212.397.0985
www.courtinnovation.org

This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Youth Involvement in the Sex Trade: A National Study
By Rachel Swaner, Melissa Labriola, Michael Rempel, Allyson Walker, and Joseph
Spadafore
© March 2016
Center for Court Innovation
520 Eighth Avenue, 18th Floor
New York, New York 10018
646.386.3100 fax 212.397.0985
www.courtinnovation.org

Acknowledgements
This study was supported by Award No. 2009-MC-CX-0001 from the Office of Juvenile
Justice and Delinquency Prevention of the U.S. Department of Justice. The opinions,
findings, and conclusions or recommendations expressed in this report are those of the
authors and do not necessarily reflect the positions or policies of the Department of Justice.
We are grateful to Ric Curtis for developing the youth interview instrument and respondentdriven sampling protocols, and for his assistance in site selection. We are also grateful to
Jennifer Bryan for her work early on in the project.
We could not have completed this project without the support, hard work, and dedication of
the site coordinators: Ric Curtis and Anthony Marcus (Atlantic City, NJ); Joshua Gamson
and Nikki Jones (Bay Area, CA); David Maurrasse and Cynthia Jones (Miami, FL); Marcus
Martin and Heather Champeau (Dallas, TX); Laurie Schaffner (Chicago, IL); and Andrew
Spivak, Brooke Wagner, and Jennifer Whitmer (Las Vegas, NV). Apart from this multi-site
report, the site coordinators completed reports for each of the six study sites providing rich
ethnographic details on their themes and findings (see
http://www.courtinnovation.org/youthstudy). We are also deeply grateful to the research
assistants at each site, who conducted the youth interviews with care and professionalism.
We thank staff at the following organizations for granting interviews to our research team so
that we could learn about the work they do. Specifically, thanks to Community Treatment
Solutions, Atlantic County Youth Shelter, and the Division of Youth and Family Services in
Atlantic City; the Center for Young Women’s Development, Standing Against Global
Exploitation (SAGE), and Lyric in San Francisco; MISSSEY and JPG Consultants in
Oakland; Children of the Night in Los Angeles; Kristi House, the Department of Children
and Family Services, Women’s Fund of Miami-Dade County, Stand Up for Kids, and the
Miami Police Department in Miami; Salvation Army STOP IT, Chicago Alliance Against
Sexual Exploitation, Night Ministry, and the Chicago Police Department in Chicago.
We also thank representatives from Statistical Analysis Centers and other state agencies for
providing aggregate and case-level data. The methodology used and results reported using
data obtained from state data sources are solely the responsibility of the research team.

Acknowledgements
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

At the Center for Court Innovation, we wish to thank Liliana Donchik for countless hours of
data entry and Liberty Aldrich and Greg Berman for their comments on an earlier version of
the report.
We also thank our grant managers over the course of this research project: Barbara Kelley,
Karen Bachar, and Chris Holloway.
For correspondence, please contact Rachel Swaner at rswaner@nycourts.gov.

Table of Contents
Acknowledgements
Executive Summary

i
v

Chapter 1.

Introduction

Chapter 2.

Research Design and Methodology

Chapter 3.

Findings from the Youth Interviews

Chapter 4.

Findings from Official Data and National Population Estimate

Chapter 5.

Perspectives of Social Service Providers and Law
Enforcement

Chapter 6.

Conclusions

References

Appendices

Appendix A.
Youth Interviews Consent Form
Appendix B.
Youth Interview Instrument

Table of Contents
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

101

iii

Appendix C.
Social Service Providers Interview Guide

126

Appendix D.
Youth Interviews: Bulleted List of Select Significant Differences by Subgroups

133

Appendix E.
Youth Interviews: All Responses by Site

136

Executive Summary
Over the past decade, federal, state, and local policymakers across the United States have
devoted increasing attention to the plight of youth who are involved in the sex trade. Despite
growing national attention, the ability of policymakers to design effective programs and
strategies has been hindered by a paucity of valid research on the size, needs, characteristics,
and criminal justice experiences of these youth (e.g., see Institute of Medicine 2013).
Funded by the Office of Juvenile Justice and Delinquency Prevention of the U.S. Department
of Justice, the current multi-method, multi-site study aims to increase scientific knowledge.
Building on prior research using comparable methods in New York City and implemented by
some of the same researchers (Curtis et al. 2008; Muslim, Labriola, and Rempel 2008; and
see, also, Dank et al. 2015), this study includes interviews with youth and official records
data collection in six sites: Atlantic City, NJ; the Bay Area, CA; Chicago, IL; Dallas, TX;
Miami, FL; and Las Vegas, NV.
To date, the study has produced six reports providing comprehensive ethnographic findings
concerning the lives of youth in the sex trade in each of the research sites (Jones and Gamson
2016; Marcus, Riggs, Rivera, and Curtis 2016; Martin et al. 2016; Maurrasse and Jones
2016; Schaffner et al. 2016; and Wagner, Whitmer, and Spivak 2016). The current report
provides a quantitative, multi-site analysis of findings from nearly 1,000 youth interviews
across all six sites; a population estimate; findings from official criminal justice data sources;
and findings from interviews with service providers. All reports are available at
http://www.courtinnovation.org/youthstudy.

Overview of the Study Methodology
This study was animated by the goal of gaining a representative portrait of the lives and
needs of youth who are involved in exchanging sex for money, food, housing, drugs, or other
goods. The study was overseen by the Center for Court Innovation in collaboration with the
John Jay College of Criminal Justice. Researchers from John Jay developed the youth
interview instrument and led the fieldwork in the Atlantic City site, and researchers from the
Center for Court Innovation contracted with experienced ethnographers to lead the fieldwork
in the five other sites and conducted the multi-site analysis presented in this report.

Executive Summary
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

The six research sites were selected to represent a geographically diverse set of locations
that, at the outset of the project, were deemed likely to possess a relatively sizable population
of youth in the sex trade. Final site selection was informed by official prostitution arrest
statistics collected by the Federal Bureau of Investigation; call volume from a national
human trafficking hotline maintained by the Polaris Project; and key informant interviews
regarding perceived national “hub sites” for the sex trafficking of underage individuals. The
feasibility of implementing the study methodology was also considered in final site selection.
The four principal elements of the study methodology are summarized below.

Youth Interviews
To interview youth in the six sites, the research team employed respondent-driven sampling
(RDS), ethnographic fieldwork, and street and internet outreach. RDS methods are designed
for interviewing populations where there is involvement in stigmatized behavior; a dearth of
widely accepted research information; and participants who are difficult to reach through
traditional sampling methods (e.g., see Heckathorn 1997, 2002, 2007).
In this study, RDS started with “seed” interviews, most of whom were recruited through
street ethnography at known “tracks” or “strolls.” The interviews were all anonymous.
Participants were paid for their time (most received $40); given three numbered coupons;
asked to give the coupons to other eligible youth in their social network; and paid $10 for
each coupon that was redeemed for a subsequent interview. The combination of street
ethnography and RDS methods allowed the research team to access a wider pool of youth
than in prior studies that exclusively recruited youth through a single venue, such as service
providers or criminal justice agencies.
In total, interviews were completed with 949 young people ages 13-24 across the six sites.1
Ranging from 30 minutes to two hours, the interviews included both closed-ended and openended questions on a wide range of topics. The present report only concerns responses to the

Restricting eligibility exclusively to underage individuals (ages 13-17) would have limited the
effectiveness of the RDS methodology, since individuals just under or over the age of 18 are
frequently networked to each other. Further, prior research in New York City and Atlantic City,
the first site in the current study, led the research team to expect limited age-based differences in
interview responses. Indeed, across all six sites, the final data in the present study pointed to few
substantive differences in the experiences of the 13-17-year-old and 18-24-year-old subgroups.

closed-ended questions and to questions that could be recoded into quantitative data. The six
site reports provide in-depth themes and findings from the open-ended questions.

Official Criminal Justice Records
For 2009, the number of prostitution arrests of youth under the age of 18 in all 50 states was
obtained from the Uniform Crime Reporting (UCR) program of the Federal Bureau of
Investigation (FBI). Given limitations in this data (see Chapter 2), comparable information
was also sought from state-based data sources; and data was obtained from the designated
Statistical Analysis Center (SAC) or some other state data source in 34 of the 50 states in the
U.S. In those states for which the arrest totals obtained from FBI and state-based data sources
diverged, the two results were averaged to create a final estimate for each state.
Additionally, the research team sought case-level data on demographics, criminal history,
prosecution outcomes, and re-arrests for youth ages 24 and under who were arrested on
prostitution charges in the six research sites. The research team also sought analogous data
on individuals arrested on commercial sexual exploitation of children charges.

Population Estimate
A national population estimate was constructed based on the number of underage individuals
arrested for prostitution in a given year (obtainable from official sources), combined with
youth interview data on the percentage of youth who are missed in official records—given
that only a fraction of youth in the sex trade are arrested each year. The methodology is
designed to correct for the underestimate of the true population that would result from
utilizing official arrest statistics alone. Nonetheless, as described in the body of this report,
the research team encountered limitations in the quality and precision of each data source,
rendering it unfeasible to produce a precise national estimate in the form of a single number.
Instead, the research team created a conservative (i.e., intentionally wide) range for a
national population estimate, varying assumptions to produce a lower and upper limit.

Service Providers and Law Enforcement
In four of the six research sites, interviews were conducted with staff from a total of 18 social
service and law enforcement agencies that interact with youth in the sex trade. (In some of
the 18 agencies, multiple staff were interviewed.) The interviews covered organizational
background; interactions between agency staff and youth; client characteristics; service
delivery; and challenges to working with the population.

vii

Characteristics and Needs of the Population
This section reports major themes and findings from the 949 youth interviews in all six sites.

Demographic Characteristics
 Gender: The interview participants displayed significant gender diversity, with 60% cis
female, 36% cis male, 4% trans female, and less than 1% trans male (6 youth total).2
 Sexual Orientation: The participants similarly identified with a range of sexual
orientations (53% heterosexual, 36% bisexual, 9% gay, and 2% other sexual orientation).
 Race/Ethnicity: More than two-thirds of the interview participants (70%) were
black/African-American. The other participants were white (12%), multi-racial (8%),
Hispanic/Latino (7%), or identified with an additional race or ethnic category (3%).
 Age: A total of 199 underage youth were interviewed (ages 13-17), accounting for 21% of
the total 13-24-year-old sample. However, pointing to a young age of initiation among
most participants, 77% of all respondents indicated that their first experience trading sex
took place while under the age of 18. (The average age was 15.8 years old.)
 Place of Birth: Only 3% of participants were born outside the United States. Most
participants entered the sex market after running away or otherwise leaving home at a
young age.
 Living Situation: Eleven percent of interview participants were either homeless/living on
the streets (5%) or living in a shelter (6%), and an additional 12% reported living alone.
The remaining 77% were living with family, friends, or in some other arrangement.
 Parent Status: Thirty percent of participants reported having children, with cis females
significantly more likely to report having children (37%) than cis males (20%) or trans
females (14%).

When someone is cisgender, they identify their gender as the gender they were assigned at
birth. When someone is transgender, they identify their gender as something other than what they
were assigned at birth. For example, someone classified as trans female was assigned male at
birth but identifies as female.

viii

Market Involvement
 Background to Market Entry: Almost three-fourths of interview participants (73%) had
left home under the age of 18, and 13% had left home under the age of 13. (The average
age having left home was 15.0 years old.) Almost one-third of participants (32%) had their
first sex experience under the age of 13. Further pointing to possible childhood trauma
among many participants, 24% (including 30% of cis females) reported that their first sex
experience was nonconsensual.
 Work Hours: Just over half of the interview participants (52%) reported working (in the
sex market) 10 or fewer hours in the previous week, 15% reported working 11-20 hours,
21% reported 21-30 hours, and 21% reported 31 or more hours.
 Weekly Income: Thirty-two percent reported weekly earnings of $300 or less—with 44%
of cis males compared to 25% of cis females and 30% of trans females reporting earnings
in this range. At the other end of the spectrum, 28% reported weekly earnings of $301$600, 21% reported $601-$1,000, and 19% reported $1,001 or more—with cis females the
most likely gender subgroup to report earnings in the higher income categories.
 Obtaining Customers: Interview participants reported obtaining customers through a
variety of means (often listing more than one), including: the street (63%), internet (42%),
friends (39%), referral from someone else they knew (26%), and a pimp (9%). The most
common internet sites used were Adam4Adam, Backpage, Craigslist, and Facebook.
 Working Conditions: More than half of the sample (53%) reported work conflicts,
including arguments with other sex workers, customers, pimps, and drug dealers. Most
conflicts were described as relating to competition and money. Thirty-five percent of all
participants recounted that they had experienced conflicts leading to physical fights, with
54% of trans females indicating as much—citing their gender identity as a basis for
discrimination and violence.

Pimps and Market Facilitators
 Definition: The six site reports make clear that interview participants were involved in
complex social relationships with others in the underground economy. To classify these
relationships for multi-site analysis, a “pimp” is defined as a person who exploits an
individual in the sex market through coercion, control, or force. A “market facilitator” is
defined as a person who helps obtain customers but without evidence of coercion, control,
or force. For coding purposes, researchers reviewed answers to a battery of both closedand open-ended questions asking participants how they obtain customers; whether they
shared their money with anyone (and who); whether that person had rules; and the nature

of those rules. Coding for a pimp was liberal, meaning that researchers likely over-coded
the presence of pimps, including cases where participants did not themselves use this term.
 Prevalence of Pimps: Fifteen percent of interview participants had a pimp. Cis females
(21%) were significantly more likely than cis males (7%) or trans females (9%) to have a
pimp who exerted coercion, control, or force. Pimps were both male and female.
 Imposition and Nature of Rules: Of those participants who had pimps, 42% reported
that their pimp had rules. Examples involved returning a percent of earnings to the pimp
each day; stopping work for the day after reaching a quota of customers (potentially with a
threat of beatings for noncompliance); and being required to obtain money from customers
upfront. Other rules involved drug use, time limits with customers, ability to have
partners, and time of day to be back at home.
 Prevalence of Market Facilitators: Nineteen percent of participants were coded as
having a market facilitator who was not a pimp. As discussed in the site reports (see, e.g.,
Marcus et al. 2016; Wagner et al. 2016) and earlier New York City studies (Curtis et al.
2008; Dank et al. 2015), typically a market facilitator and the youth do not share money,
have no rules, and neither works for the other. The parties find the relationship to be
mutually beneficial, leading often, for example, to mutual support, discussions of
strategies to stay safe, and cross-referrals of potential customers.
 Legal Definition of Trafficking: Eighty percent of participants met the legal definition of
sex trafficking at some point in their lives, either because they had a pimp or, in most
cases, because they were under the age of 18 when they first traded sex. At the time of the
interview, 32% met the legal definition of trafficking.

Interactions with Law Enforcement and Other Illegal Activities
 History of Arrest: Overall, 65% of participants reported a prior arrest, 16% reported a
prior prostitution arrest, and 11% reported a prostitution arrest in the past year. Those with
a pimp were significantly more likely to report a prostitution arrest than others (28% v.
13%).
 Arrest Charges: Interview participants who had been arrested reported a diverse array of
charges. More than four-fifths (82%) were nonviolent. Charges other than prostitution
included property crimes (41% of all charges, including many low-level theft charges);
drug-related crimes (22%), and trespassing or loitering charges (8%).

 Experience of Transgender Youth: Trans females (37%) were significantly more likely
than cis males (12%) or cis females (17%) to report a prior prostitution arrest and at least
three times more likely to report a prostitution arrest in the past year (30% v. 9% v. 10%).
 Drug Use: Nearly three-fourths (73%) of participants reported currently using at least one
illegal drug, including marijuana (66%), cocaine/crack (13%), heroin (7%), or some other
drug (often methamphetamines or pills, 20%).

Interactions with Social Services and Major Service Needs
 Physical Health: Most participants reported positive indicators of physical health,
including having seen a doctor within the past three months (64%) or within the past year
(93%), and using protection against pregnancy and sexually transmitted infections (94%
reported “all the time” or “often”).
 Experiences with Services: About half (51%) of participants reported having ever been
to a service agency (48% of cis males, 51% of cis females, and 71% of trans females).
 Major Service Needs: The services sought most by participants involved basic survival
needs: employment or education (49%); housing or help paying for utilities (47%), and
food or money (36%). By comparison, counseling or advice was sought by 16% of
interview participants and addiction or health services by 11%.
 Exiting the Life: Sixty-two percent of participants had tried to leave “the life” and 63%
reported that they would know how to leave they life if they wanted to do so.

Differences by Site
Themes and patterns were broadly consistent across sites with several notable exceptions.
Specifically, the average age of the Miami sample was younger than in the five other sites
(17.6 years v. 19.9 years) and more likely to be born outside the U.S. (8% v. 1%). In the Bay
Area, a significantly higher percentage of interview participants worked with a pimp than
elsewhere (29% v. 12%). In Atlantic City and Las Vegas, relationships with market
facilitators were particularly common (36% in Atlantic City and 24% in Las Vegas,
contrasting with 15% in the other four sites). Finally, social services appeared to be more
plentiful in the Bay Area than elsewhere. Seventy-five percent of Bay Area interview
participants reported having ever visited a service agency, compared to 46% in the other five
sites. Participants in the Bay Area were also significantly more likely to report that staff from
a service agency had approached them with an offer of services (35% v. 19%).

The Criminal Justice Response
This section reports official arrest, prosecution, and recidivism outcomes—both for youth
ages 13-24 who are engaged in the sex trade and individuals who exploit these youth for
commercial gain.
 Underage Prostitution Arrests Nationwide: Combining FBI and state data sources
yields an estimate of 1,130 individuals under the age of 18 who were arrested for
prostitution in 2009. These arrests were spread unevenly, with 67% of all arrests taking
place in five states: California, Nevada, New York, Texas, and Washington.
 Arrest History and Recidivism: In all four sites where case-level data was obtained on
youth under the age of 25 who were arrested for prostitution (Chicago, Dallas, Las Vegas,
and Miami), at least 56% had a prior arrest, and at least 36% were re-arrested over a twoyear period. Notably, well over half of all prior and recidivist arrests were for offenses
other than prostitution. In Chicago, for example, the sample averaged 1.33 re-arrests on
any charge compared to 0.54 prostitution re-arrests over two years; and in Dallas, the
sample averaged 1.02 re-arrests on any charge compared to 0.37 prostitution re-arrests.
 Prostitution Case Outcomes: In sites providing data on prosecution outcomes for youth
under the age of 25 who were arrested for prostitution, the percent convicted was 28% in
Miami, 56% in Dallas, 58% in Chicago, and 59% in Las Vegas. Of those convicted, the
percent receiving jail time was 39% in Miami, 73% in Chicago, and 97% in Dallas.
 Characteristics of Defendants Arrested on Exploitation Charges: Across 11 states for
which such data could be obtained, 607 defendants were arrested on commercial sexual
exploitation of children-related charges in 2009, of which 65% were male and 35% were
female. This gender distribution was generally mirrored in four of the five research sites
for which relevant data was available (excluding Atlantic City); defendants ranged from
60% to 71% male in four sites, although they were 96% male in Las Vegas.
 Case Outcomes and Recidivism in Exploitation Cases: Conviction rates in commercial
sexual exploitation of children cases varied (12% in Las Vegas, 31% in San Francisco,
43% in both Chicago and Dallas, and 55% in Miami). The two-year re-arrest rates on any
charge also varied (9% in Las Vegas, 36% in Chicago, 39% in Dallas, and 50% in Miami).
 Problematic Data Collection on Underage Arrests: Focusing on aggregate data
concerning the number of underage prostitution arrests in each state, this study uncovered
substantial limitations in data quality. They included: incomplete reporting of arrest
numbers from local law enforcement to the Uniform Crime Reporting (UCR) program of

xii

the FBI (the low charge severity of prostitution offenses makes reporting optional); laws
in some states that group together prostitution, exploitation, and solicitation charges under
a single penal law code; the UCR practice of combining arrests in the aforementioned
three categories within the same overarching “prostitution and commercialized vice”
designation even where state penal laws could have enabled distinguishing prostitution,
solicitation, and exploitation charges; and general limitations in the existence and
reliability of data on juvenile (as opposed to adult criminal) arrests in some states.
Moreover, in 15 of 34 states for which both UCR and state-based data sources provided
numbers for underage prostitution arrests, including ten of 14 states where one data source
yielded a number of arrests greater than five, the UCR and state-based numbers diverged.

Population Estimate
Combining information from state and federal data sources yielded a total of 1,130 underage
prostitution arrests in 2009. Youth interview data yielded 10.75% of interview participants
reporting an arrest for prostitution in the prior year. Extrapolating from these numbers yields
a national population estimate of 10,506 youth under 18 years of age who are engaged in the
sex trade nationwide. A second estimate was produced by first obtaining the percent of
participants reporting a past year arrest within each site and then giving equal weight to each
site’s result (rather than according more weight to sites where we interviewed more youth).
This second approach yielded an estimate of 12.67% youth with a past year prostitution
arrest, which extrapolates to a total of 8,914 youth in the sex trade nationwide. Given notable
data limitations, we then varied our underlying assumptions to produce a population estimate
range with a lower limit of 4,457 youth and an upper limit of 20,994 youth. A particular
concern leading to this conservative range, as opposed to single estimate, is that youth in
tightly controlled situations may not have been located for interviews by the research team
and, more relevant to the population estimate algorithm, may also not tend to be located or
arrested by law enforcement.3 To address this potential bias, the upper limit of the population
estimate range reflects a conservative assumption that only 5.38% of the true underage
population of interest is arrested for prostitution each year.

Interview data did not, per se, provide support for the premise that youth who are subject to
control are inaccessible to law enforcement, as those involved with a pimp were more than twice
as likely as others to report a prior arrest for prostitution (28% v. 13%). Nonetheless, it remains
plausible that those whose daily movements are subject to a deeper level of control than the
individuals represented in our sample are distinctly inaccessible to law enforcement.

xiii

The Perspective of Social Service Providers
This section reports on themes and findings from interviews conducted with staff at select
social service and law enforcement agencies.
 Varying Perceptions of the Population: Staff varied in the extent to which they defined
the population of interest as female and as working with a pimp. In general, staff from
agencies that specialize in serving this population tended to perceive that the majority of
these youth are female and work with a pimp, whereas staff from agencies that do not
specialize primarily in this population tended to perceive the population as more diverse.
 Contended Nature of Language: Staff from some agencies referred to the population
with the term “commercial sexual exploitation of children” or “CSEC.” Staff at these
agencies also generally tended to use the term “victim” and expressed a view that most of
the population is female. Staff from other agencies used the term “youth engaged in
survival sex,” which one interviewee from a homeless shelter defined as “trading sex for
money, drugs, or housing.” Staff from still other agencies used the language of the youth:
“sex work,” “hookin’ and crookin’,” “hustling,” or “other job.” There was also tension
around the term “trafficking,” which some interviewees objected to for variety of reasons
(e.g., suggesting that it directs attention to international as opposed to domestic forms of
trafficking; or dovetails with labeling the youth as “victims,” potentially depriving them of
agency).
 Constraints on Policy and Practice Related to Funding: Some staff expressed that the
need to secure funding often required agencies to create singular narratives that tended to
limit both discourse and programming to a subset of all youth and, in particular, to focus
on girls. Some staff perceived that policymakers would be less willing to move away from
criminalizing youth unless they perceived that the population consists predominantly of
girls who are subject to force.
 Available Services: Service agencies whose staff were interviewed reported offering a
variety of services, although they tended to fall into the following categories: counseling,
support groups, case management, job assistance, parenting classes, and legal and
educational advocacy. Those interviewed expressed that youth have a particular unmet
need for safe housing to reduce vulnerability to entry or to help youth exit “the life.”
 Additional Service Agency Needs: Social service staff expressed particular needs for
more staff who could engage in visible outreach to the youth population (i.e., in lieu of
merely waiting for participants to locate and arrive at the door of services themselves);
more bilingual staff; more staff education around trauma in the juvenile justice system;
and more engagement with the youth on what is best for them.

xiv

Conclusion
From speaking with almost 1,000 youth in six sites across the country, this study revealed
that young people who are engaged in the sex trade are a diverse population that does not
conform to any particular stereotype. The population varies in gender, sexual orientation, and
living situation, among other attributes. Some members of the population work long hours
and earn a sizable weekly income from their sex market participation, but a great many do
not. The population is often involved in complex social relationships that, for a vast majority,
does not involve direct coercion, control, or force—but often involves others who find
themselves in broadly analogous positions in the underground economy.
Many in the population of interest use one or more illegal drugs and have an arrest history
for an array of low-level illegal behaviors that are not limited to prostitution or related
offenses. Of those youth who are underage—and, indeed, most of the youth we interviewed
first entered the sex market when they were underage—most have not been arrested for
prostitution per se, although many have an arrest history on other charges. Thus, whereas an
estimated 1,130 underage youth were arrested for prostitution in 2009, even the lower limit
in our range of national population estimates is more than four times higher, given that most
youth do not experience a prostitution arrest in any given year.
Just as many of the involved youth are not arrested for prostitution, many also have not
accessed services. (Almost half reported never accessing services). Unfortunately, the
greatest service needs that the youth reported—which included the socioeconomic and
survival necessities of safe housing, employment, education, food, and money—are not the
most easily met needs, given the current funding and resource environment, which tends to
place a greater emphasis on counseling, therapy, support groups, and legal advocacy.
We found that most youth who enter “the life” have limited options available to
them. Most left home at a young age, many experienced severe forms of childhood trauma,
and their skills and capacity to leave “the life” and enter the mainstream routines of stable
housing, education, and legal work are limited. Even those youth who are not subjected to
emotional, sexual, or physical violence by a pimp are still disadvantaged by social structures
(including poverty and discrimination) that restrict available life choices and leave some
youth particularly vulnerable to entry into the underground economy and “the life”—and
may pose seemingly overwhelming barriers to exiting the life.

The prevailing narrative about young people engaged in the sex trade is that they are young
girls controlled by pimps. While a notable percentage of the population fits this description,
many do not. Our research suggests that many are male or transgender. The majority do not
have pimps. The vast majority are from the United States rather than other countries. Helping
these various subgroups escape “the life” will require more than a single, generic model; it
will require policymakers to create multi-faceted initiatives that grapple with the realities on
the ground—including how this young population conceives of itself.

xvi

Chapter 1

Introduction
Over the past decade, youth involvement in exchanging sex for money has become a
growing concern among youth advocates, policymakers, and researchers across the United
States. Federal, state, and local policymakers have responded with an array of initiatives,
including expanded federal and state enforcement of those who exploit underage youth for
commercial gain; training for law enforcement in identifying the involved youth; services for
female youth in particular; specialized human or sex trafficking courts that seek to connect
youth involved in the commercial sex industry with court-ordered services; and interagency
task forces designed to coordinate action across advocates as well as the criminal, juvenile
justice, child welfare, and social service systems (see Banks and Kyckelhahn 2011; Finklea,
Fernandes-Alcantara, and Siskin 2011; Finn et al. 2009; Monto 2004; Muslim, Labriola, and
Rempel 2008; Siskin and Wyler 2013; Small et al. 2008).
To date, there has been a paucity of rigorous research on the size, needs, and characteristics
of the relevant population of youth who exchange sex for money. The absence of an
evidence-based and representative understanding of the involved youth has hindered the
ability of those who care about this population to design relevant programs and to make
informed policy decisions. Accordingly, the Institute of Medicine’s recent report,
Confronting Commercial Sexual Exploitation and Sex Trafficking of Minors in the United
States (2013), called for rigorous research to advance understanding in order to create more
informed prevention and intervention strategies and better law enforcement responses.

About This Study
The current study, funded by the Office of Juvenile Justice and Delinquency Prevention of
the U.S. Department of Justice, aims to increase scientific knowledge concerning youth who
engaged in the sex trade. Utilizing a mixed method approach of collecting official arrest and
prosecution data, interviewing service providers, and conducting in-depth interviews with
youth and slightly older young adults in six sites (Atlantic City, NJ; Dallas, TX; Las Vegas,
NV; the Bay Area, CA; Miami, FL; and Chicago, IL), the goals of the study are:

Chapter 1. Introduction
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 1



To provide a rich qualitative and quantitative portrait of the characteristics, experiences,
and health and social service needs of these youth;



To analyze arrest patterns and prosecution and recidivism outcomes for these youth when
they encounter the juvenile or criminal justice systems;



To document the types of services that are available to this population; and



To estimate the size of the national population of youth who are engaged in the sex trade.

Six separate reports provide systematic qualitative accounts of the emergent themes and
findings from the youth interviews that were conducted in each of the six respective research
sites (Marcus, Riggs, Rivera, and Curtis 2016; Jones and Gamson 2016; Schaffner et al.
2016; Martin et al. 2016; Maurrasse and Jones 2016; Wagner, Whitmer, and Spivak 2016).
This publication constitutes a multi-site synthesis and final technical report on the study.
Authored by researchers at the Center for Court Innovation, this report describes the research
methodology for each component of the study; reports findings from both a 50-state (national
scope) and six-site analysis of official arrest data; analyzes prosecution and recidivism
outcomes in select sites; synthesizes themes and findings from social service provider
interviews; and provides comprehensive quantitative findings from the youth interviews. The
qualitative, but not the quantitative, findings from the youth interviews are the primary focus
of the six aforementioned site-specific reports. Therefore, the current report focuses in
somewhat greater detail on presenting an original quantitative analysis. For this report and
the six site reports, see http://www.courtinnovation.org/youthstudy.
Chapter 1 of this report reviews the relevant literature to date. Chapter 2 describes the multisite research design and methodology. Chapter 3 presents findings from interviews with
youth in our six sites. Chapter 4 presents findings from the official records analysis of arrest,
prosecution, and recidivism data; it also includes a population estimate for the entire United
States. Chapter 5 presents an analysis of social services, including services currently
available as well as challenges and youth needs that are not currently being met. The report
concludes in Chapter 6 with a summary of findings, lessons learned for policymakers and
practitioners, and recommendations for future research, policy, and practice.

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The Hidden Nature of the Population
Young people involved in the sex trade are often difficult to locate and reluctant to
acknowledge their age (Spangenberg 2001). These youth may have contact with myriad
agencies, including law enforcement, criminal courts, juvenile courts, child welfare agencies,
educational institutions, shelters, and a wide range of service providers (Muslim et al. 2008).
Except in jurisdictions with rigorous systems for interagency communication—which by
many accounts are rare—different agencies may each encounter a subset of the population
(Muslim et al. 2008; Finn et al. 2009). In turn, researchers who draw a sample or conduct a
study based on youth who come into contact with only one system (law enforcement,
juvenile detention, child welfare, or social services) may reveal only part of the population
and only part of the story.
In the absence of a comprehensive research sample, several studies have sought information
from service providers (Estes and Weiner 2001; Gragg et al. 2007; Williamson et al. 2010).
Yet, many of the youth involved in the commercial sex market may be resistant to services;
unaware or unable to find services that meet their needs; or unable to escape from their
exploiter in order to reach services safely. Hence, those who end up at the door of service
agencies may not be representative of the population overall. A representative sample may be
even less likely to emerge from arrest or court statistics—population estimates that rely on
criminal justice data may be biased by the particular arrest and prosecution policies in those
jurisdictions where research is conducted (see Puzzanchera al. 2011).
At the time of the first International Congress against the Commercial Sexual Exploitation of
Children (CSEC) in 1996, the research literature was described as plagued by problematic
methodologies (Ennew et al. 1996). While the situation has improved, a consensus has yet to
emerge on the magnitude of the problem or the characteristics or needs of the population,
either domestically or internationally. Policymakers and service professionals need more
detailed information about the attitudes, orientations, and behaviors of these youth in order to
develop effective responses.

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Population Estimates
The extant literature has produced a small number of national population estimates, all of
which have serious methodological limitations, as well as several state and local estimates, of
which several of the most scientifically rigorous are summarized below.

National Population Estimates
Perhaps the most widely cited population estimate comes from the research of Estes and
Weiner (2001). They estimated that between 244,000 and 325,000 children are at risk of
commercial sexual exploitation in the United States, in addition to the additional estimated
105,000 children who are victims of other types of child sexual abuse annually. To produce
their population estimate, Estes and Weiner (2001) conducted interviews and focus groups
with “runaway and throwaway” youth living on the streets, as well as interviews and focus
groups with a number of state, local, and federal law enforcement agencies, social service
providers and others. Surveys were sent to hundreds of local, state, and federal agencies.
Despite this mixed-method approach, the limitations of Estes and Weiner’s (2001) estimates
are well documented (see, e.g., Stransky and Finkelhor 2008) and are clearly acknowledged
by the authors. For instance, the estimates are based on youth whom are “at risk” for
commercial sexual exploitation; the estimates are not based on actual youth engaged in the
commercial sex market. In tallying “at risk” youth, individuals may belong to multiple risk
categories (homeless, gay, victim of child sexual abuse, etc.). These young people would be
counted multiple times in the estimates. The authors did not take into account individuals
who may belong in multiple risk categories (Stransky and Finkelhor 2008). Although the
authors describe how the methodology corrects for some portion of the duplicate counts, the
true extent of duplicate counting cannot be known. The authors themselves acknowledge that
“a different type of study from ours—one that used a different methodology and a higher
investment of resources—is needed to carry out a national prevalence and incidence survey
that could produce an actual headcount of the number of identifiable commercially sexually
exploited children in the United States” (Estes and Weiner 2001: 143).
Another study attempting to produce a national prevalence estimate analyzed the National
Longitudinal Study of Adolescent Health, a nationally representative sample of 13,294
adolescents enrolled in grades 7-12 in the United States (Edwards, Iritani, and Hallfors
2006). This study found that 3.5% of youth reported that they had ever exchanged sex for

Page 4

drugs or money. The median number of times that youth who have exchanged sex reported
doing so was one. Critiques regarding the wording of questions in the study, in particular the
possible misunderstanding of what it means to exchange sex for goods, have been raised
(Stranskey and Finkelhor 2008).
Some estimates draw upon law enforcement data sources. In particular, Finkelhor and
Ormrod (2004) analyzed police reports of juvenile prostitution cases from 1997 through
2000. They found that 200 prostitution incidents reported in the National Incident Based
Reporting System (NIBRS) from 1997-2000 involved juvenile offenders. Mitchell, Finkelhor
and Wolak (2010) built upon this earlier work and surveyed a national sample of law
enforcement agencies about the characteristics of crimes involving juvenile prostitution and
the numbers of arrests and detentions for these crimes during a one-year period. They
produced a national estimate of 1,450 arrests or detentions in cases involving juvenile
prostitution during a one-year period (Mitchell, Finkelhor and Wolak 2010). Of course, not
all youth who exchange sex for money or other goods are arrested. And when arrests do take
place, many law enforcement agencies charge the youth with offenses other than prostitution,
such as drug possession or a curfew violation (Smith, Vardaman, and Snow 2009). Just as the
Estes and Weiner estimate of at-risk youth is almost surely far higher than the actual number
of youth in the population, the Mitchell et al. estimate likely omits a large swath of the
population who are not arrested for prostitution in a given year.
Finally, Smith, Vardaman, and Snow (2009), working with local human trafficking task
forces, provided an estimate of underage sex trafficking in ten Department of Justice-funded
sites. While this study did not produce a national estimate, the study reported findings for ten
key hub cities. The estimates used a different measurement period in each site and relied
largely on official government records. From 1994-2007, Smith et al. (2009) estimated that
there were 5,122 individuals suspected to have been sex trafficking victims in Las Vegas, but
no more than 227 for each of the nine other sites, which Kansas City, Dallas, Fort Worth,
San Antonio, Salt Lake City, Buffalo, Baton Rouge, Tampa, and one site in the northern
Mariana Islands.

Local Population Estimates
A series of case studies have examined the problem in central hubs across the county. Most
of the findings from these studies are based on official arrest records or convenience samples

Page 5

of interview subjects; they do not indicate the extent of “hidden” youth who exchange sex for
money.
New York City: Possibly the most studied “hub” is New York City. Beginning with the
mayoral administration of Rudolph Giuliani (1994-2001), all “adult establishments,”
including stores specializing in sexually explicit magazines, books and videos, as well as
strip clubs and peep shows, had to be located at least 500 feet apart from each other and at
least 500 feet away from churches, schools, and residential districts. These establishments
were also restricted from operating in certain commercial and manufacturing districts. The
regulations severely limited the number of adult establishments located around Times Square
and significantly reduced street prostitution in the Midtown area (Sviridoff et al. 2000),
displacing much of the sex business away from Manhattan and into the outer boroughs
(Spangenberg 2001).
In January 2002, the next mayor, Michael Bloomberg, announced “Operation Clean Sweep,”
with the purpose of abolishing “quality of life” problems by targeting repeat offenders with
high numbers of arrests, including those involved with prostitution. But as law enforcement
devoted more attention to pursuing the street-level sex market and their participants, the sex
business adapted and diversified, becoming reliant on technological innovations such as the
internet and cell phones to conduct business. While New York City can rightfully claim to
have made progress in addressing the most blatant sex markets (e.g., in and around Times
Square), there is scant evidence that the overall sex market across the city has been reduced
in size. Indeed, professionals and child advocates have become concerned that the population
of exploited youth in New York City has grown in recent years (Covenant House 2013).
Spangenberg (2001) estimated that in 2001, there were up to 5,000 youth who were sexually
exploited in New York City. Another more recent study, based on a comprehensive survey of
social service and public sector agencies, estimated that the population of sexually exploited
children in New York City was approximately 2,200 (Gragg et al. 2007). Since many
exploited youth are unlikely to have had direct contact with the agencies surveyed, the
authors believed that their methodology probably yielded a significant undercount of the
actual population.
Indeed, in 2008, researchers from John Jay College of Criminal Justice (as part of a larger
study conducted in partnership with researchers on the current project) conducted a
population estimate using respondent-driven sampling (RDS). RDS uses a network-based

Page 6

strategy for accessing and interviewing statistically representative samples of hard-to-reach
populations, such as young people involved in the commercial sex market, by recruiting
eligible “seed” interviewees who then refer others they know to be interviewed for the study
to build a sample pool. The 2008 study (Curtis et al. 2008) estimated that there were 3,946
children ages 18 and younger in New York City who were exchanging sex for money or
other goods. An original reanalysis of the same dataset by the current research team, which
engaged in a small number of methodological corrections, changes the estimate to 2,726.
Atlanta: A team of researchers sought to estimate the prevalence and scope of child sexual
exploitation in Atlanta. Multiple estimation methods produced a surprisingly low set of
figures (Finn et al. 2009). Over a four-year period from September 2003 to September 2007,
the study identified only 24 prostitution-related arrests of youth under 18. The study also
found that only one in 12 homeless youth participating in research interviews had engaged in
sex for money; only 15 youth whose cases were documented in a citywide interagency
tracking system had experienced forms of child sexual exploitation; and only 2.3% of 697
surveyed social workers, psychologists, and other Atlanta area counselors reported having
served youth with a history of involvement in the commercial sex industry. This estimate
seems low for Atlanta and was not based on a representative sample drawn from all
institutions that might conceivably have contact with the relevant population.
Another study conducted in Atlanta, Georgia surveyed street activity, internet service
postings, escort services, and large hotels for juvenile prostitution during a one-month period
(The Schapiro Group 2010). Surveying street activity involved video recording of individuals
suspected to be engaged in prostitution. Researchers also counted adolescent females in
advertisements on Atlanta Craigslist and placed their own ads looking for youth prostitutes to
count response rates. To study escort services, researchers called escort service phone
numbers throughout Georgia. To study hotel activity, researchers were placed in lobbies of
major hotels in the Atlanta area. The researchers counted that on any given night, there were
41 girls under age 18 involved in street activity, 26 girls involved in Craigslist sex postings,
20 girls involved in escort services, and 7 girls selling sex in major hotels, for a total of 94
girls under 18 per night. The utility of these numbers in informing a general population
estimate for Atlanta is unclear, absent further information about the behavior of this
population.
Ohio: The Ohio Trafficking in Persons Study Commission Research and Analysis SubCommittee examined data from the Innocence Lost Initiative and from Immigrations

Page 7

Customs Enforcement, reviewed governmental and nongovernmental reports and studies,
and spoke with social service workers. Similar to Estes and Weiner (2001), the authors
developed low, medium and high risk categories to determine the number of American-born
youth at risk for trafficking in Ohio, as well as the number of foreign-born youth that have
been trafficked (Williamson, Karandikar-Chheda and Barrows 2010). They arrived at an
estimate of 2,879 American-born youth in Ohio at risk of sex trafficking, over 1,000 of
which are estimated to be currently trafficked in the state. Since the methodology closely
mirrors that of Estes and Weiner (2001), similar caveats apply, especially concerning the
distinction between at-risk youth and participants in the sex trade. In addition, youth can
easily be placed in one or more of the three tier categories and, thus, counted multiple times.
Also in Ohio, information from the Ohio Network of Children’s Advocacy Centers shows
that 51 minors from across the state were potential human trafficking victims over a ninemonth period, including five youth under the age of six. The network has a state contract to
screen children referred by law enforcement, children’s services agencies and others, to
determine whether they may have been trafficked. Statistics from July 2013 to March 2014
showed all but five of the 51 minors reported were 13 to 18 years old. Only one case
involved a male. They came from both urban and rural areas of the state. Information on at
least three of the five youngest victims indicated they were trafficked sexually by one or both
of their parents in exchange for drugs, rent, goods or money (Ohio Network of Children’s
Advocacy Centers 2014).

Population Characteristics and Needs
Numerous studies have been conducted on the causes and correlates of youth involvement in
the commercial sex market in general and prostitution in particular. These studies have
identified a host of underlying factors, including childhood abuse (e.g., Busby et al. 2000;
Edwards et al. 2006; Estes and Weiner 2001; Greene et al. 1999, Schissel and Fedec 1999;
Williamson 2009); runaway status (Edwards et al. 2006; Greene et al. 1999; Kennedy and
Pucci 2009; Seng 1989; Simons and Whitebeck 1991); and exposure to criminal behavior,
drug use, and domestic violence (Burgos et al. 1999; Kennedy and Pucci 2009; Schissel and
Fedec 1999; Silbert and Pines 1982).
Child prostitution may further exacerbate the risks of drug use (Edwards et al. 2006; Inciardi
et al. 1991); unplanned pregnancy and sexually transmitted diseases (Busby et al. 2000;
Decker et al. 2012; Ireland and Widom 1994; Kidd and Krall 2002, Schissel and Fedec

Page 8

1999); physical and sexual abuse (Schissel and Fedec 1999, Simons and Whitbeck 1991;
YWEP 2009); and criminal behavior (Loeber and Farrington 1998; Widom and Kuhns
1996). Finally, psychological problems such as depression, self-abusive behavior, and
schizophrenia may either cause or result from youth involvement in the commercial sex
market (e.g., Brannigan and Brunschot 1997; Kennedy and Pucci 2009; Schissel and Fedec
1999; Seng 1989). Professionals continue to struggle with the challenges posed by these
youth, including flight risks and lack of willingness to cooperate in investigations; in many
places, there is a lack of appropriate housing to keep these youth safe and provide them with
much needed services (Kennedy et al. 2007).
There is broad agreement concerning many of the causes and correlates of youth
involvement in the sex market. Yet, many questions related to the characteristics, needs, and
experiences of the population during the period when they are actively involved in the sex
market remain unanswered. Moreover, since much of the research focuses on young people
that are referred to social services or housed in juvenile detention centers or other criminal
justice settings, there is a need to provide a more representative examination of this
population.
The more that data analysis is not limited to a particular slice of the population (e.g., those
who are arrested or those who appear at the door of available service agencies), the more that
boys appear to comprise a significant percentage of the overall population. Indeed, in
analyzing the National Longitudinal Study of Adolescent Health, a nationally representative
sample of 13,294 adolescents enrolled in grades 7-12 in the U.S., researchers found that 68%
of those who involved in the sex trade were male (Edwards et al. 2006).
In recent years, more research is focusing on LGBTQ youth. Ashley (2008) found that
transgender youth reported that prostitution was a kind of “game” or “competition.” They
also reported that being in “the life” made them feel included and part of a family. Some
reported that they faced employment hurdles due to their gender, so selling sex was a way to
survive. Participatory action research conducted by the Young Women’s Empowerment
Project also found that girls were denied help from institutional systems, such as the
Department of Children and Family Services and the police, because of their sexual
identification (YWEP 2009). According to a recent study of LGBTQ youth engaged in the
commercial sex market in New York City, 47% identified as male, 36% as female, 11% as
trans female, 3% as trans male, and 3% as other (Dank et al. 2015).

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Another issue yet to be resolved is the extent to which the youth who are involved operate
independently or work for a true “exploiter.” In a New York City-based study that involved
respondent-driven sampling interviews, 10% of those who exchange sex for money worked
for a market facilitator or “pimp” (Curtis et al. 2008). A cross-sectional survey of female
patients in five family-planning clinics (affiliated with Planned Parenthood) in Northern
California found that of the 9% of young women (aged 16-29 years old) who sought services
at these family planning clinics, 16% reported pimp involvement (Decker et al. 2012).
However, an acknowledged limitation in the methodology in both of these studies was the
potential for under-representing youth who were trafficked into the country or held in tightly
controlled indoor environments.

The Law Enforcement Response
There is little research to indicate how frequently youth are arrested and prosecuted for child
prostitution. In general, evidence indicates that prostitution providers are arrested far more
frequently than their customers and procurers (Thukral and Ditmore 2003). Several cities
have attempted to address this disparity (Monto 2004), but some believe that only federal
standards can ensure consistency (Estes and Weiner 2001). However, a recent study
concludes that because prostitution-related offenses are regulated at a state level, the federal
law is rarely applicable (Lutnick 2016). In many cases, police charge the young person with
another crime, like loitering or disturbing the peace, in places where prostitution for minors
has been decriminalized (Lutnick 2016). Law enforcement officials often state that arresting
these minors is for their own good, to get them away from their pimp and off the dangerous
streets, but this recent research suggests that involvement with the criminal justice system
only leads to additional barriers, such as employment, education, housing and benefits and
not to safety or the ability to escape an exploiter (Lutnick 2016; YWEP 2009).
To facilitate a consistent response, specific laws such as the Victims of Trafficking and
Violence Protection Act of 2000 (TVPA) and the Prosecutorial Remedies and Other Tools to
end the Exploitation of Children Today Act of 2003 (PROTECT) were created to define and
address youth engaged in the sex trade. TVPA, in particular, states that any person below 18
years old “induced to perform” a commercial sex act is considered a victim of a “severe form
of trafficking” and the crossing of state lines is not required for it to be designated a federal
crime. The TVPA and its reauthorizations in 2003, 2005 and 2008, as well as the PROTECT
Act of 2003 and the 2008 Adam Walsh Act, have funded task forces to better identify
victims, increase penalties for perpetrators, and enhance victim services.

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In addition to the federal statutes, all states have laws addressing various aspects of
commercial sexual exploitation and sex trafficking of minors, although most states do not
mention those terms in particular. A much smaller subset of state laws, usually those enacted
more recently, contain specific provisions that address sexual exploitation or sex trafficking
of minors or the particular situation and needs of those minors who have been victimized.
A recent study found that since the passage of the new federal statutes, many jurisdictions,
especially in California, Florida, and Texas, saw a significant increase in the number of
investigations, case filings, and convictions where a prison sentence is imposed for
exploitation (Small et al. 2008). The study found that it was not just the passage of this
legislation that led to these increases, but the creation of task forces and convening of
national summits that brought an increased awareness and focus on prosecuting the
perpetrators using a collaborative, victim-centered approach.
Another step towards a national response was taken in 2003 with the Federal Bureau of
Investigation’s Innocence Lost initiative. This initiative re-conceptualizes prostituted
children as victims and focuses on providing them with services, while increasing legal
responses to the adults who exploit them. This re-conceptualization is reflected in a range of
local initiatives, such as passage of the Safe Harbor for Exploited Children Act in New York
in 2008, and the recent rise of specialized prostitution, human trafficking, and sex trafficking
courts that seek to help youth who are arrested through court-ordered services. Nonetheless,
it is unclear whether available services are truly suitable or effective or whether the use of
“back-end” policies after a youth is arrested will truly reduce or inadvertently dovetail with
the criminalization of the involved youth.
With regard to enhancing efforts to prosecute the exploiters, some evidence suggests that
new policy initiatives have produced positive results. On a national scale, the average federal
prison sentences imposed on exploiters recently increased from 53 months in 1999 (prior to
when the TVPA went into effect) to 80 months in 2004 (Small et al. 2008). Over that same
time, the percentage of offenders receiving probation (i.e., non-custodial) sentences
dramatically decreased. A quasi-experimental analysis of a specialized prosecution initiative
of the District Attorney’s Office in Queens, New York confirmed that it resulted in a
significant increase in jail or prison sentences imposed on those convicted of exploitation
offenses (Muslim et al. 2008).

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Available Services for Youth
A wide array of barriers hinder efforts to provide effective assistance to youth engaged in the
sex trade, beginning with the hidden nature of a significant portion of the population and
continuing with resource and funding limitations to the provision of crisis housing and other
services (Gragg et al. 2007; Muslim et al. 2008; Lutnick 2016)). The complexities of their
lives may bring these youth into contact with multiple institutions: criminal justice, child
welfare, health care, and education. Furthermore, providers who work with youth have
expressed concern about training deficits for clinical staff, police officers, and judges (Gragg
et al. 2007). Existing services range from enforced detention programs (Busby et al. 2000) to
shelters and safe housing (e.g., Children of the Night; Office of the United Nations High
Commissioner for Human Rights) to voluntary counseling, health, educational, and job
training services.
More than two-thirds (68%) of youth who were interviewed in one of the New York City
studies reported having visited at least one service agency; many reported visiting multiple
agencies (Curtis et al. 2008). Yet, little research has been conducted into the efficacy of
services for this population (Wahab 2005). One evaluation of the Salt Lake City’s First
Offender Prostitution Program made a number of recommendations, including that programs
balance the priorities of criminal justice and service agencies; use empirically-driven,
structured intervention strategies; limit the scope of issues to be addressed; train counselors
to deal with sex work issues; and establish clear goals, objectives, and roles for staff (Wahab
2005). Impact studies could not be located, however, that employed rigorous quasiexperimental methods and included re-offense or similar outcomes.

On Language: A Challenge for Researchers,
Policymakers, and Practitioners
Throughout our research, we came across numerous words and phrases to describe the
population of interest for our study, including: commercially sexually exploited children,
youth engaged in survival sex, child sex workers, child or juvenile prostitutes, teenage
hookers, or trafficking victims. Many of these terms entail non-empirically-based
assumptions or do not accurately capture everyone in the population.

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In the current study, we conducted interviews with 949 young people ages 13-24 who
exchange sex for money, housing, food, or drugs. In the remainder of this report, we
generally refer to this population simply as “youth engaged in the sex trade,” although we
recognize that this language too is imperfect. As our research indicated, some youth often
exchange sex outside of a commercial sex market and are instead exchanging sex for things
other than money, including housing, food, drugs, or some other good. More broadly, our
intention is to be inclusive of anyone who was eligible for our study, where eligibility
encompassed youth ages 13-24 who exchange sex for either money or some other good.

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Chapter 2

Research Design and Methodology
This study was animated by the goal of providing a better understanding of the lives,
experiences, and needs of the wide range of young people (ages 13-24) engaged in the sex
trade in the United States. In addition, the project assesses the criminal justice response to
this population, analyzing arrest numbers in all 50 states and prosecution and recidivism
outcomes for both the youth and exploiters in select sites. Finally, the project seeks to
provide information regarding the total size of the population of interest. The study was
designed and overseen by the Center for Court Innovation in collaboration with the John Jay
College of Criminal Justice. Researchers from John Jay developed the youth interview
instrument and led the fieldwork in the Atlantic City site. Researchers from the Center for
Court Innovation contracted with experienced ethnographers to lead the fieldwork in the five
other sites and conducted the multi-site analysis.
The study involved four concurrent research strategies: (1) respondent-driven sampling
(RDS) methods to locate and interview youth engaged in the sex trade in six sites across the
country; (2) collection and analysis of prostitution-related arrest nationwide; (3) collection
and analysis of prosecution, sentencing, and recidivism data in research sites where relevant
data could be obtained; and (4) interviews with select representatives from service providers
and law enforcement agencies in four of six sites. This chapter outlines the design and
methodology of these four strategies. Relevant limitations to the methodology are described
within the sections that follow.

Youth Interviews
The lead research agency, the Center for Court Innovation had previously teamed up with
researchers from the John Jay College of Criminal Justice to conduct a similar study on
youth in New York City (Curtis et al. 2008; Muslim et al. 2008). The current study sought to
replicate much of the New York City study. After first outlining the site selection process,
we provide an overview of the cross-site research methodology that built on the past
experience of the research team.

Chapter 2. Research Design and Methodology
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 14

Site Selection
The youth interview component of this study occurred in six sites around the United States:
Atlantic City, NJ; Bay Area (San Francisco and Oakland), CA; Miami, FL; Dallas, TX;
Chicago, IL; and Las Vegas, NV. Each site was initially tasked with seeking to complete
200-300 interviews with young people engaged in the sex trade. At each site, a local
professor or consultant was hired as a site coordinator to oversee a team of research
assistants (often local graduate students) to conduct the interviews.
The Atlantic City site was chosen as a pilot for the following reasons: 1) as the second
largest gaming market in the United States, it stands second only to Las Vegas in its
reputation as a hub for prostitution and related illegal leisure activities; 2) with the only nocharge beach in New Jersey and a boardwalk that runs nearly the length of the island, the city
is, during the summer months, a magnet for runaway youth; and 3) a robust sex market (not
specifically youth though) was detected in early reconnaissance trips. The site was also
attractive as a pilot site due to its proximity to New York City, where the research team was
located.
To determine the other five sites, a multi-step process was implemented. First, general
research was conducted on the prevalence of youth engaged in the sex trade using
information provided by the Federal Bureau of Investigation and the Office of the Inspector
General. This first step allowed for the development of a short list of possible sites based on
official prostitution arrest numbers of people under the age of 18 (FBI Uniform Crime
Report) and the 13 high-intensity child prostitution areas identified by the FBI’s work with
the Innocence Lost project (Office of the Inspector General).
Second, the research team spoke with key stakeholders at two leading organizations. The
Polaris Project coordinates the national human trafficking hotline, provides client services
through specialized local offices, and runs campaigns to fight human trafficking. During our
discussion with Polaris, the research team confirmed the short list of sites with the numbers
Polaris was receiving from its hotline.
Discussions were also held with Shared Hope International. At the time of site selection,
Shared Hope International was finalizing field assessments designed to measure and evaluate
the access to and delivery of services for youth who were involved in the commercial sex
market. The field assessments involved interviewing justice officials, non-

Page 15

governmental/service provider organizations, and child protection organizations regarding
how the involved youth are identified and routed through the criminal justice or social
service systems. Shared Hope International conducted field assessments in select sites, and
three (South Florida, Las Vegas, and Dallas) were also on our short list.
The final sites were confirmed after receiving recommendations for local site coordinators
who could serve as effective partners. Leading each site was a large responsibility and it was
critical to work with individuals that came highly recommended, knew the community and
key players, had strong qualitative research experience, and had the ability to manage
research assistants.

Rationale for Respondent-Driven Sampling
Respondent-driven sampling (RDS) was first introduced by Heckathorn (1997) as a method
for sampling hard-to-reach populations whose underlying behavior or participation in
research might be stigmatized (Heckathorn 1997, 2002, 2007). RDS works as follows: Initial
“seeds,” intentionally recruited by the researchers, represent Wave 0. These seeds must meet
sample eligibility criteria but do not have to be “representative.” Each seed then recruits a
limited number of other eligible participants (e.g., three to five), who comprise Wave 1; they
in turn recruit similar numbers of additional participants (Wave 2); and so forth.
Research has shown that sample and social network characteristics reach equilibrium—i.e.,
become representative of the population of interest—after several waves. The precise number
of waves can range from three to six, depending on the number of subjects recruited by each
initial subject and other factors; although some research suggests that six waves is the
maximum necessary (Heckathorn 1997, 2002; Salganik and Heckathorn 2004; Wang et al.
2005). RDS relies on the fact that respondents have more study-eligible members in their
social networks than the number of persons they are allowed to recruit. Thus each
recruitment wave introduces an element of randomness, which, as the process continues, is
magnified by subsequent, quasi-random choices (since individuals must recruit individuals
who have not already been interviewed). The process ensures that after many waves, any bias
that results from initial seed selection is minimized (Heckathorn 1997, 2002; Salganik and
Heckathorn 2004). To be clear, the essential finding of the RDS literature is that although
RDS begins with a convenience sample composed of several “seed” interviews, when
implemented properly, RDS ends with a snowball sample that, after making statistical
adjustments for network size (and hence increased or decreased likelihood of being recruited

Page 16

for the study), can make a strong claim to represent the population of interest.
Youth engaged in the sex trade fit the profile of groups for which RDS was originally
designed—lack of prior, widely-accepted information about the population; involvement in
stigmatized behavior; often difficult to reach through traditional sampling methods; and a
small subset of the total youth population (e.g., meaning that random sampling methods
would require extraordinarily large sample sizes, mostly of ineligible individuals, to reach
the target group). Previous research suggests that the population of interest is indeed heavily
“networked,” and in fact, prior efforts to use RDS with this population have been at least
partially if not highly successful (e.g., Curtis et al. 2008; Dank et al. 2015).

Logistics and Limitations
Full descriptions of each site’s RDS implementation and recruitment strategies, as well as
challenges in applying the methodology, are discussed in the six individual site reports (see
Jones and Gamson 2016; Marcus, Riggs, Rivera, and Curtis 2016; Martin et al. 2016;
Maurrasse and Jones 2016; Schaffner et al. 2016; Wagner, Whitmer, and Spivak 2016). In
this section, we present a basic overview of major cross-site decisions and challenges.
In each of the sites in the present study, initial research “seeds” were recruited through
multiple methods, including local service providers, street outreach on known “tracks” or
“strolls,” flyers, internet posts, and ethnographic methods. At the start of this study, site
coordinators were advised by the Center for Court Innovation research team to recruit
participants through local social service providers (e.g., youth organizations that have
programs specifically for sexually exploited youth, homeless/street youth shelters, LGBT
centers, etc.). This proved to be a challenge, as some providers were leery of having their
participants help recruit others who were “still in the life.” Additionally, those engaged in
services were often no longer networked to others in the sex trade. For these reasons, site
coordinators eventually moved to outreach and ethnography to recruit participants. In the last
two sites to initiate fieldwork, Chicago and Las Vegas, the site coordinators began with
outreach and ethnography immediately from the outset.
Once initial seeds were recruited and interviewed, they were paid for their time. In the early
stages of the study, participants were given $20 for an interview. However, with Institutional
Review Board (IRB) approval, this was soon increased to $40 in an effort to build the
interview pool. After each interview, participants were given three numbered coupons and

Page 17

told to give the coupons to young people in their network who were also eligible for the
study. In the early phases of study implementation, eligibility meant young people ages 1319 who engaged in the sex trade. However, this age range proved limiting: often people older
than 19 were networked to those who were younger, and by not interviewing someone who
was 20 years old, we missed the opportunity to become connected to truly eligible youth.
Additionally, the numbers of people in the 13-19-year-old age range proved to be low in our
pilot site, Atlantic City. Therefore, we increased the maximum age eligibility to 24. As
indicated in the results presented in Chapter Three, the empirical data pointed to few
substantive differences in the needs and characteristics of our population based on age,
retrospectively justifying the decision to expand eligibility through age 24.
The coupon design varied by site, but all included a number to contact the local research
team to set up an interview. When coupons were redeemed by eligible research subjects,
their recruiter could be compensated $10 for each one (they would call the contact number to
find out if their coupons had been redeemed). The eligible subjects referred by the seeds
were in turn given three coupons to recruit eligible participants in their network. If enough
coupons were not returned to generate recruitment trees, more seeds were recruited.
Although this RDS referral system had proved successful in past studies, including the
research team’s prior study of the same population in New York City, the system was
unsuccessful in several sites in this study. For instance, in the Bay Area site, 66% of the
interviewees were seeds. In the Dallas site—where the lack of population density, the lack of
available public transportation options, and the high usage of cars meant that youth were not
geographically networked in a way that RDS requires—nearly all of the interviews were
seeds.
While the total number of interviews varied by site, only two sites totaled over 200. Table
2.1 presents the total number of eligible participants interviewed by site. There may be a few
reasons for the lower than expected Ns. First, in some sites (e.g., Atlantic City), it seems
likely that the total number of youth who engaged in the sex trade was simply lower than
expected. Second, there may be seasonality in some sites (e.g., Atlantic City or Miami),
where warmer weather may create an influx of runaway youth. If the research team was
actively recruiting during colder months, the population of young people may have indeed
been lower, making recruitment difficult. Third, there are members of the population who
may either not be visible (e.g., under strict control by a pimp), or may not speak English or
Spanish (e.g., there was a sizeable Russian-speaking population in Atlantic City), which were

Page 18

the only two languages in which interviews could be conducted. Researchers in Atlantic City
were in the field for significantly fewer months than the other sites, and part of that time was
when the age eligibility was limited to 13- to 19-year-olds, limiting sample size in our pilot
site. Finally, a delay in the project for over a year broke recruitment trees that did exist in
Chicago and Las Vegas, and when the project started up again, research deadlines meant that
three sites ultimately had to conclude fieldwork (Chicago, Las Vegas, and Dallas) before
reaching the initially desired N.
As shown in Table 2.1, despite lower than expected volume at the site level, close to 1,000
interviews were conducted in total, and for most analytic purposes, site data could be pooled.
Pooling the site data yielded estimates with relatively small confidence intervals, although
required drawing attention to a relatively small number of substantive issues where responses
in some sites did systematically differ from others (see Chapter 3; and see Appendix E).
Except where delineated in Chapter 3, we largely uncovered comparable patterns across
sites, providing a strong justification to take advantage of our large sample size when
pooling.
Table 2.1 Eligible Participants Interviewed by Site
Site
N
Atlantic City, NJ
98
Bay Area, CA
136
Miami, FL
264
Dallas, TX
78
Chicago, IL
202
Las Vegas, NV
171
TOTAL
949

Informed Consent and Confidentiality
Upon meeting a potential interview participant, research interviewers briefly screened the
youth to ensure study eligibility. Then, interviewers went over the informed consent form.
An example of this form is attached as Appendix A. The interviewer was tasked with
conducting a quick assessment of participants’ psychological state of mind, physical
condition, the degree to which they appeared to fully understand the purpose of the study, the
extent to which they assented to participate, and the relative degree of freedom that they

Page 19

appeared to exercise in making decisions. (To facilitate the assessment process, all research
assistants first participated in training concerning both the research methodology and
underlying psychological problems and dynamics that the interviewers might encounter in
the population.) If the participant was of sound mind, safe, and fully understood the study,
they would sign a fake name of their choosing to the consent form.
Participants were often concerned that their information would be shared with police officers
or other law enforcement officials. Interviewers assured them about the confidentiality and
anonymity of their participation4. No identifying information was collected, and interviews
were conducted in safe spaces, often chosen by the participant to ensure privacy, safety, and
comfort.
At each site, a social worker was on call in case a participant became upset, although in the
nearly 1,000 interviews that were conducted, no one had to call the social worker. A local
resource sheet was provided to participants if they wanted it at the end of each interview.
This study was approved by the Center for Court Innovation’s Institutional Review Board.
Additionally, the Institutional Review Boards at the University of North Texas Health
Science Center at Fort Worth and the University of Nevada, Las Vegas approved the studies
in Dallas and Las Vegas, respectively.

Interview Instrument
The interview consisted of the following domains: 1) demographic characteristics (14
questions, including race/ethnicity, age, living situation); 2) market involvement (28
questions, including age and means of initiation, location of work, and type of involvement);
3) network size and characteristics (15 questions, including information about pimps and

4 This study and its resulting knowledge could not be gained without our having the capacity to
assure our human subjects that they could speak freely—without fear that we might abrogate
their confidentiality, report them to child protective agencies, order them to services, or involve
the police without a compelling justification. Moreover, in this particular study, the names of
those we interviewed were not requested and, therefore, were not known even to the researchers,
which provides our interviewees with an added confidentiality protection. Additionally, federal
regulation 28 CFR Part 22 makes clear that researchers must maintain the confidentiality of their
data without any exceptions—including child abuse. Therefore, maintaining the anonymity of the
interviewees was essential for this study.

Page 20

customers); 4) health and social service history and needs (14 questions); 5) experience with
law enforcement and courts (12 questions, including number of arrests, charges, and
arrest/court outcomes); and 5) future expectations (10 questions). The questions were a mix
of closed-ended and open-ended. This report includes only the closed-ended questions and
questions that could be coded into quantitative data. For more narrative qualitative data, as
well as themes and findings emerging from the full transcripts and exchanges during the
research interviews, see the individual site reports that accompany this report (Jones and
Gamson 2016; Marcus et al. 2016; Martin et al. 2016; Maurrasse and Jones 2016; Schaffner
et al. 2016; Wagner et al. 2016). Interviews lasted between 30 minutes and two hours and
were most often conducted one-on-one. Occasionally, an additional interviewer was present.
Interviews mostly took place in local parks, fast-food restaurants, universities, cars, and
community spaces. If the participant consented, the interview was recorded for later
transcription. The interview instrument is attached as Appendix B.

Analysis
All quantitative data were entered into databases. Sites were given the option of entering
their youth interview data into Access, Excel, or Dedoose. After all data were entered,
research staff at the Center for Court Innovation merged the databases into SPSS, then
cleaned and coded the data. Chapter 3 of this report presents the descriptive (i.e.,
quantitative) findings for the 949 youth ages 13-24 in the total sample. Bivariate t-test and,
where appropriate, chi square analyses were conducted to determine significant mean
differences based on various demographic variables (e.g., gender, age, or whether someone
was a parent) and certain experiences (e.g., whether someone’s experience in the commercial
sex market involved force, fraud, coercion, or control). ANOVA was used to test for
significant differences across interview sites.
To achieve a truly representative sample with RDS, when analyzing quantitative data, the
researcher omits seed interviews (Wave 0). However, because the majority of interviews in
our study were from seeds, we did not eliminate seed interviews. Additionally, weighting is
often used during analysis to compensate for the fact that some people have larger networks
than others and hence have more opportunities to be recruited for the study. However,
weighting was unfeasible in this study due to the lack of precise question wording that
accounted for networks from a relevant age range (13-24 for the complete study sample).
This weakens our internal validity, or ability to yield precise estimates for our sites.

Page 21

Official Arrest and Conviction Data
Official arrest, prosecution and recidivism data were collected to achieve multiple goals. To
achieve the goal of generating a valid prevalence estimate of the size of the relevant
population of youth, RDS methods require youth interview data to be analyzed in light of
data collected from an institutional dataset. For this purpose, information about the aggregate
number of youth prostitution arrests in each state and nationwide in 2009 was obtained from
a combination of national (Federal Bureau of Investigation) and state data sources. Having
obtained this information, it becomes possible to estimate the number of youth who trade sex
in each state and nationwide, whether or not the youth have an arrest history per se.
Case-level official records were also sought in the six states where the interview sites were
located. These case-level records allowed an analysis of prosecution and recidivism
outcomes for both the youth and individuals charged with exploitation offenses in the
selected research sites.

Relevant Offenses
Research was conducted to determine the specific penal law charges in each state that might
be applied to young people under the age of 18 (as well as 18 and over) as well as to
exploiters and solicitors. Shortly into the data collection process, however, the research team
realized that not all states had codes that were easily delineated into the three relevant charge
categories of (1) prostitution, (2) solicitation, and (3) exploitation (where the latter is often
termed “promoting prostitution”). Furthermore, although many state legal codes had these
charge delineations, many state agencies were unable to provide data by state legal code, and
instead provided us with data by the federal code. That is, rather than separating out different
prostitution-related charges, these states combined all prostitution-related charges into the
category of Prostitution and Commercialized Vice. In total, 16 states provided data for this
more general category, potentially encompassing those arrested for prostitution, solicitation,
or exploitation. Further, in four additional states, Delaware, Hawaii, Rhode Island, and
Tennessee, the state’s prostitution penal codes combine buying and selling, making the
distinction impossible between prostitution and solicitation arrests.
To summarize, the penal laws in many states fundamentally precluded generating an accurate
and separate estimate of the prevalence of prostitution, exploitation, and solicitation arrests.

Page 22

Some of these data limitations are mitigated for the purpose of estimated underage
prostitution arrests. In short, it seems reasonable to expect that underage youth charged with
any prostitution offense were generally arrested, specifically, due to trading sex, not due to
soliciting sex or seeking to promote prostitution or exploit other underage youth.
Nonetheless, despite this a priori expectation, it remains the case that in some states, some
number of underage individuals whose offenses involved solicitation or exploitation may
have been included incorrectly in the prostitution numbers due to the fashion in which data
had to be obtained.

Aggregate Data Collection from the Uniform Crime Reporting
Program of the Federal Bureau of Investigation
For each state, we received the number of prostitution arrests of youth under the age of 18
from the Uniform Crime Reporting (UCR) program of the Federal Bureau of Investigation
(FBI). Of particular note, prostitution charges in some states are defined only as ordinance
violations, not even rising to the misdemeanor level, a factor that may decrease the likelihood
of rigorous and complete reporting to the UCR program. In addition, the UCR data includes
the category, Prostitution and Commercialized Vice, which encompasses prostitution,
solicitation, and exploitation arrests (see discussion just above). Nonetheless, the availability
of the UCR data in all 50 states meant that at least an estimate could be provided for each
state regardless of the availability of data from a state-based data source.

Aggregate Data Collection from State-Based Data Sources
In addition to the UCR numbers, we believed that it was essential to collect data from statelevel Statistical Analysis Centers (SAC). Given that law enforcement agencies may not
engage in complete reporting of prostitution arrests to the UCR program of the FBI, our
expectation was that in at least some states, the Statistical Analysis Center-based information
would be more complete and accurate. To obtain estimates from state sources, we first
contacted each state’s Statistical Analysis Center. In those cases where the SAC did not have
the appropriate data, other agencies such as the state’s Department of Public Safety or State
Police were contacted. In one state (Hawaii), it was necessary to contact separate agencies
for adult criminal and juvenile arrest data.
In general, once we identified the appropriate agency and contact person, we sent a request
for data. The request specified which penal codes, years of arrests, and other demographic

Page 23

data (including age, gender, and race and/or ethnicity of the offender) were needed for our
analysis.
We requested aggregate data on the number of arrests of underage individuals (under the age
of 18) in 2009 from 44 states as well as the District of Columbia. For the six remaining
states, where our youth interview sites were located, we requested case-level, rather than
aggregate, data. After extensive follow-up contacts (follow-up e-mails, calls, etc. directed to
multiple potentially relevant agency personnel in each state), we received data from 34 states
in total. Specifically, aggregate or case-level data was obtained from 19 SACs,5 nine
Department of Public Safety or State Police offices,6 four Attorney General’s Offices,7 two
Governor’s Offices,8 and one Crime Reporting Unit (from Massachusetts). (As noted above,
two separate data sources were needed for Hawaii.) States that did not provide data included
Arizona, California, Colorado, Georgia, Iowa, Indiana, Kansas, Louisiana, Mississippi, New
Hampshire, Nevada, Ohio, Oklahoma, South Carolina, Vermont, and Wisconsin.
Washington, D.C. also did not provide data. Notably, although Nevada could not provide
data for the underage population of primary interest, as discussed below, Nevada provided
case-level data for 19-24-year olds who were arrested on prostitution charges within the Las
Vegas research site. In general, lapses in our capacity to collect necessary data from statelevel data sources in 16 states were caused by, in some states, our inability to locate and
contact correct and responsive agencies, and in others, an inability of the appropriate
agencies to provide the data.
Of the 34 states that did provide data on youth under the age of 18 who were arrested for
prostitution, some were also able to provide a breakdown by charge, age of the youth,
defendant demographics (e.g., sex, race/ethnicity, and place of birth), dispositions (e.g.,
dismissed vs. convicted) and sentences (e.g., prison, jail, probation, time served, conditional
discharge, fine, or other).

The states providing SAC data included Alabama, Arkansas, Delaware, Florida, Hawaii, Idaho,
Illinois, Kentucky, Missouri, Montana, Nebraska, New York, New Jersey, Oregon, South
Dakota, Tennessee, Texas, Virginia, and West Virginia.
6
The states whose public safety or police offices provided data included Alaska, Connecticut,
Maine, Michigan, Minnesota, New Mexico, Pennsylvania, Utah, and Washington.
7
States include North Dakota, Rhode Island, and Wyoming.
8
States include Maryland and North Carolina.

Page 24

Case-Level Prosecution and Recidivism Data
In addition to obtaining data spanning all 50 states in the U.S., we were also interested in
assessing the criminal justice response to young people who trade sex, specifically, analyzing
prosecution and recidivism outcomes for the youth and their exploiters. To achieve this goal,
we requested case-level data from the six states where the youth interviews took place.
First, we contacted each of the six state’s Statistical Analysis Centers. We requested 2008
and 2009 case level data for all people arrested in the state with prostitution related penal
codes (including child prostitution, exploitation, or solicitation of a minor—but with each of
these charge sub-types distinguished). Specifically, we asked for the following variables:
arrest and conviction charges, case processing time, dispositions, sentence types, sentence
length, and background characteristics (age, gender, race, ethnicity, place of birth, criminal
history, county and jurisdiction). To satisfy the requirements for the population estimate (i.e.,
one full year of official records data), we used the 2009 data. However, we asked the state to
identify the 2008 sample for the recidivism analyses (the 2008 sample allowed additional
recidivism tracking time). Thus, the descriptive information presented in Chapter 4 and
utilized for the population estimate is based on 2009 arrests, and the recidivism information
is based on 2008 arrests.
Each data obtained from each state had important limitations. Specifically:


California: We were only able to obtain aggregate data for San Francisco County but
could not obtain usable case-level data, nor aggregate data for the state or Alameda
County, the latter of which includes Oakland. (Thus, UCR data was utilized for
estimating the annual number of underage prostitution arrests in California.)



Nevada: We could not obtain case-level data on juvenile cases or sentence information.



New Jersey: We could not able to obtain recidivism data, and other case-level data
appeared to be problematic, leading Atlantic City, NJ results to be omitted from most
portions of Chapter 4.



Florida: We could not obtain detailed jail sentence information.

Page 25

Analysis
Using the case-level data obtained from the six states, we conducted descriptive analyses,
including demographic information; distribution of specific arrest charges; percent of cases
ending in conviction vs. dismissal; sentence types (local jail, state or federal prison,
probation, etc.); and average length of custodial sentences. In addition, separately for
individuals facing exploitation charges, more limited descriptive analyses were conducted.
Re-arrest rates were computed overall and for youth arrested on prostitution charges within
each interview site. We also distinguished re-arrests on any charge from prostitution-specific
re-arrests. Furthermore, we conducted multivariate analyses to determine the individual-level
predictors of continued prostitution involvement. (These latter analyses did not reveal
substantively notable findings or patterns that were not evident from simple descriptive or
cross-tabulation analyses and, therefore, were not ultimately included in this report.)

Population Estimate
As described above, we possessed youth interview data containing information about
whether and how often youth are arrested for prostitution, and we possessed official arrest
data concerning actual prostitution arrests in the six research sites as well as all 50 states
nationwide. This information made it possible to compute a population estimate by
combining knowledge of the number of individuals factually arrested for prostitution with
knowledge—gained through the youth interviews—of the percent of individuals in the
population of interest who experience a prostitution arrest in any given year. In effect, the
percent of youth within the interview sample who reported a prostitution arrest over a oneyear period provides an indication of the extent to which the number of official arrests in a
given year in fact covers the total population. To provide a hypothetical example, if 10% of
youth participating in interviews reported an arrest for prostitution over the prior one-year
period, and official arrest records reveal that there were factually 100 youth prostitution
arrests over a comparable one-year period, we would project that 100 would be equal to 10%
of the actual population in the jurisdiction in question; hence, our population estimate would
be that 1,000 youth are involved in the sex trade in the jurisdiction. In general, such a method
is referred to as a “capture-recapture” methodology. Originally developed in biology
(Kendall 1999), this method has been applied widely in social sciences (Bouchard and
Tremblay 2005; Bouchard 2007), including in prior studies of prostitution (Curtis et al 2008;
Roberts and Brewer 2006).

Page 26

Of course, as was the case in this study (see above), data can be flawed. In the above
hypothetical example, 10% of those youth who were interviewed reported an arrest; but what
if we were disproportionately likely to find and interview youth who had been arrested as
opposed to youth who had not been arrested? In other words, what if, in reality, the real
percent arrested in the past year was 5%, not 10%? Plugging in 5% would yield a population
estimate for the jurisdiction of 2,000, rather than 1,000. Conversely, if the real percent
arrested in the past year was 20%, the population estimate would be reduced to 500. As
further discussed below, allowing that the numbers plugged into our formulas are all subject
to various forms of sampling error, we opted to include a range for all reported results. We
also opted to make the reported range conservative (i.e., wide), such that it would be
extremely unlikely that the real number could be lower than the lower limit of the range or
higher than the upper limit of the range (although the possibility of even larger deviations
than what is reflected in our range cannot be ruled out entirely). As will become clear in
Chapter 4, the upper limit of the range was likely well over the actual number, but given
multiple data uncertainties, an unusually prudent and conservative sensitivity analysis
nonetheless seemed preferable to producing a range that could possibly be too narrow.

Applying the General Methodology
To construct a plausible population estimate (P), there are three requirements: 1) a sample (s)
of the population of interest; 2) a known statistic derived from that sample (σ), and 3) an
equivalent statistic for the population of interest (Σ), where P = Σ / (σ /s). Applied to the
current study, the sample (s) could be drawn from youth interviews in the six sites; the
known statistic (σ) could consist of the number of youth in the sample who reported an arrest
for prostitution in the past year; and the equivalent statistic for the population of interest (Σ)
could consist of the actual number of prostitution arrests over a one-year period of time, as
determined through official records data collection for all 50 states. More specifically, two of
the relevant terms in the above mathematic formula can be combined, such that what is
essentially sought from the youth interview data is the percentage of youth in the underage
population of interest that experiences a past year prostitution arrest (σ/s).
In establishing the required statistics from the youth interviews, because the total number of
youth ages 13-17 from our youth interview sample who reported a past year prostitution
arrest was very low (17), and was even lower within each of the six sites, we deemed it more
reliable to base our calculations on the 18-24-year-old subgroup. This subgroup yielded

Page 27

larger sample sizes and hence smaller confidence intervals both overall and within each site.
Therefore, as shown in Table 2.2, the sample population (s) was the 642 youth ages 18-24
who were interviewed and who provided a valid, non-missing response to the interview
question about whether they were arrested for prostitution in the past year. The known
statistic for this sample (σ) was the number, of those 642 youth, who reported affirmatively
that they were in fact arrested for prostitution in the past year, where such number was equal
to 69. Therefore, the percentage of the sample with a past year prostitution arrest was 69/642
= 10.75%.
Since this percentage afforded equal weight to each youth with valid interview data, those
sites where we interviewed more youth disproportionately influenced this percentage. This
disproportion could well be appropriate if more individuals in the population of interest were
located in the sites where we conducted more interviews; yet, it is also possible that other
factors related to the implementation of the RDS methodology in different sites led to
variations in site-specific sample sizes. In that case, affording equal weight to each individual
would be problematic. Thus, as an alternative approach, we also calculated the percentage of
those arrested for prostitution in the past year separately within each interview and then
computed an average of the six resulting percentages site (see the percentages provided in
Table 2.2, second column from the right). This second method gave equal weight to each of
the six sites, rather than to each individual in our pooled sample. The alternate σ/s was
12.67%.
The data in Table 2.2 further illustrates how the estimation process works by providing the
number of individuals arrested for prostitution in each site and across all six sites combined
(total arrests = 1,899 for the six sites combined) and then providing population estimates (P)
for the 18-24-year-old population. However, the 18-24-year-old population estimates in
Table 2.2 (rightmost column) are mainly presented for illustrative purposes. The ultimate
purpose of this estimation process was to generate a reasonable prevalence estimate for the
underage population that trades sex. In this regard, the key result at this point was simply to
estimate the percentage of the population of interest with a past year prostitution arrest (σ/s =
10.75% or 12.67%). Notably, whereas discussions in this chapter (see, also, below) make
clear that the underlying data utilized to compute this percentage has multiple limitations, our
methodology of concluding the population estimate process with a range rather than a single
“answer” was deemed sufficient to encompass plausible error.

Page 28

In completing this estimation process, it was necessary to establish a known statistic for the
national underage population of interest (Σ), which was equivalent to a statistic available in
our sample (σ). Specifically, we obtained the number of prostitution arrests of underage youth
in all 50 states in 2009.9 State data came from state data sources and the UCR program of the
FBI, as discussed above. In states where only FBI data was available, we used the FBI
number. If both state-based and FBI data were available, we used the average of the two
numbers. As shown in Chapter 4, for each state, a population estimate was then created. A
national estimate was created by summing all 50 states’ estimates.

Table 2.2. Population Estimates for Youth Ages 18-24 in Youth Interview Sites
σ (# in sample
∑ (official
s
reporting past
number of
Site
(sample
year
people
σ /s
size)
prostitution
arrested for
arrest)
prostitution)
Atlantic City 18-24-year-olds
53
9
0
16.98%
Miami 18-24-year-olds
125
19
182
15.20%
Bay Area 18-24-year-olds
116
11
455
9.48%
Dallas 18-24-year-olds
43
9
506
20.93%
Chicago 18-24-year-olds
163
15
304
9.20%
Las Vegas 18-24-year-olds*
142
6
452
4.23%
642
69
1,899
10.75%
Total

P
(population
size
estimate)
0.00
1,197.37
4,798.18
2,417.56
3,303.47
10,697.33

* Official arrest data were only available for 19-24-year-olds in Las Vegas. The number of 18-year-olds in Las Vegas was
therefore imputed based on ratios of 18- to 19-24-year-olds in Dallas, Miami, and Chicago. This extrapolation influences the
452 figure for the number of 18-24-year-olds arrested for prostitution in the past year in Las Vegas and the 10,697.33 figure for all
those ages 18-24 who trade sex in Las Vegas but has no influence over any underage population estimates (18 and under).

Data Limitations
There were numerous limitations to our ability to generate a reliable estimate, which is why
we present a range at the end of Chapter 4 rather than a single figure.

No data were available for Washington, D.C.; therefore, the estimates represent all 50 states but
not the District of Columbia.

Page 29

Limitations Related to Youth Interview Data: First, the relevant year covered in the
youth interview data was not identical to the year covered in the official data. Specifically,
the exact question we asked of the youth was: “Within the past year, how many times were
you arrested for prostitution-related charges in this city area?” From this question, the
percent arrested would simply be the percent reporting at least one past year prostitution
arrest. The youth interviews yielding this statistic were conducted between 2010 and 2014
(although fieldwork only extended beyond 2011 in Dallas, Chicago, and Las Vegas and only
extended beyond early 2012 in Chicago and Las Vegas). This means that “past year” arrest
data could range from 2009 through 2014 depending on the site—potentially six years. For
example, if a youth was interviewed in 2010, past year arrests could take place in parts of
2009 or 2010. If a youth was interviewed in 2014, past year arrests could take place in parts
of 2013 or 2014. The official records data we obtained for the population estimate, however,
was based on 2009 data—spanning the initial portion of the potentially relevant period of
time. Yet, for the population estimate to be precise and fully capable of avoiding any historic
biases that could result from changes in law enforcement practices over time, the timeframes
referenced must match. Moreover, for interviews conducted in 2011 and beyond (i.e., not
including any part of 2009 within the “past year” period of interest), independent evidence
suggests that this might lead to an overestimate of the population of interest. Solely relying
on UCR data, the numbers point to significantly fewer prostitution arrests of underage youth
over time, declining from 1,130 arrests in 2009 to 850 in 2010, 798 in 2011, and 657 in 2012.
The UCR website includes an explicit caution against conducting trend analysis, given the
UCR reporting problems described above. Nonetheless, the UCR trend data is at least
suggestive of a potentially declining underage population that is subject to arrest over the
period of time when fieldwork took place. For purposes of the population estimate math, this
trend data, in effect, suggests that the numbers utilized for underage prostitution arrests,
because they are based on the period when fieldwork first began, may be biased somewhat
high, potentially leading the resulting population estimates to be biased high.
An additional concern related to the use of interview data is that capture-recapture methods
depend on a representative sample of a given population. However, as discussed above, all
seed interviews remained in our final sample, and we did not weight the data, posing a threat
to any claims to represent a precisely representative sample of youth who trade sex within
our six sites. Finally, the population estimation methodology involves extrapolating the
percentage of youth in the population of interest who had a past year arrest from the six sites
to the entire United States. Obviously, arrest rates in other jurisdictions as well as the true
average for the country as a whole may differ.

Page 30

Limitations Related to Official Data: The official prostitution arrest data was limited in
several ways. First, all official data collected through both the UCR program and state-based
data sources was case-level data, whereas the numbers from the interview sample used to
create the percentage of youth who experience a past year prostitution arrest (σ /s) are from
individual-level data. For example, state level data could report 15 arrests, but this number
could represent between one and 15 youth (i.e., the same youth could have more than one
arrest). This data limitation means that it is possible that we overestimated the size of the
population of underage youth who were arrested for trading sex.
Second, as discussed above, UCR data combined prostitution, solicitation and exploitation
charges, as did data from some states. Even though solicitors and exploiters are generally
unlikely to be underage, meaning that the data is still likely to fall in close proximity to the
prostitution total, underage solicitors and exploiters cannot be assumed to be non-existent.
Moreover, available case-level data in three sites that carefully distinguished the age of each
defendant facing exploitation or promoting prostitution charges revealed that the percentage
of such defendants under the age of 18 was zero in Chicago, 4% in Miami, and 3% in Texas.
This empirical data suggests that there are indeed likely to be few underage exploiters mixed
with underage individuals trading sex in data sources that ostensibly combine the categories.
Nonetheless, to the extent that we are counting some individuals arrested on exploitation or
solicitation charges towards the underage prostitution total, this data limitation too leads to
the potential for overestimating the actual underage population in the sex trade.
Third, also as discussed above, arrest numbers obtained from the UCR program may be
lower than reality due to inadequate reporting from local law enforcement agencies to the
UCR program. It is similarly possible that some state-based data sources did not capture all
juvenile arrests. This fourth bias raises the potential for underestimating the population by
omitting arrests that our data sources did not report. Moreover, while official data evidently
carries multiple biases, these biases may cancel each other out to at least some degree, since
they respectively point to possibilities both of over- and under-counting in any given state.
Nonetheless, it cannot be assumed that any canceling out of biases in different directions
ultimately leads to a precisely accurate final estimate.
Fourth, we were unable to obtain official arrest data for Oakland. Therefore, the estimate in
Table 2.2 for the Bay Area site only includes San Francisco data, although interviews were
conducted both in San Francisco and Oakland. This fourth limitation does not influence the

Page 31

national population estimate, for which official records data was required at the state level,
not the site level, and California data was successfully obtained via the UCR program.
Fifth, in our Las Vegas site, official arrest data were only available for 19-24-year-olds.
Therefore, we had to impute the number of 18-year-olds based on ratios of 18- to 19-24-yearolds in Dallas, Miami, and Chicago. Similar to the Bay Area data limitation, this one also did
not influence our national population estimate, which relied on Nevada statewide data.
Sensitivity Analysis: Given the number and potential significance of these limitations, to
increase the reliability of the reported results, all population estimate findings are provided in
terms of a range with both a low-end and high-end estimate. The use of a conservative range
takes into account plausible errors in each direction introduced by data limitations.
Furthermore, the lower and upper limits of the final population estimate range exceeded what
would have been reached through a more standard sensitivity analysis approach, which might
have relied on standard errors or a 95% confidence interval for the key statistic required from
the interview sample: namely, the percent of the population with a past year prostitution
arrest. For example, a 95% confidence interval around the estimated 10.75% statistic with a
past year prostitution arrest would have yielded a range of 8.1% to 13.3%. Nonetheless, the
final range of population estimates was instead based on a more conservative assumption at
one end of the spectrum that only 5.38% of the true population of interest in fact had a past
year prostitution arrest and an assumption at the other end that 25.34% had such an arrest.
The 25.34% figure resulted from doubling the average of the higher of the two primary
percentages arrested (2 * 12.67% = 25.34%). The 5.38% figure, whose use yields the upper
limit of our population estimate range, reflected half of the lower of the two primary
percentages arrested (0.5 * 10.75% = 5.38%). The upper limit reflects our concern that a subpopulation might exist in tightly controlled in indoor locations that was neither reached for
interviews in our study nor is commonly arrested by law enforcement.

Service Provider and Law Enforcement
Interviews
The final component of this study involved interviewing service providers, as well as law
enforcement officials, to learn more about the programs and services currently available for
this population, what service providers see as the greatest needs for the youth, and how
criminal justice players talk about and respond to this population.

Page 32

In each of the sites where youth interviews were conducted, relevant service providers and
law enforcement officials were identified (through referrals and Internet searches). Center for
Court Innovation staff reached out to potential interviewees to provide information about the
study and to see if an interview could be scheduled. If someone consented to an interview, a
date, time, and location was set for an in-person interview. The relatively open-ended
protocol included questions about organizational background; service delivery; and
challenges. Additional questions were asked related to known locations (e.g., tracks or
strolls) where youth could be found. These latter questions helped inform outreach for youth
interview recruitment. Protocols for these interviews can be found in Appendix C. These
interviews were conducted in 2010 and 2011. Researchers interviewed staff at a total of 18
social service and law enforcement agencies.10
Qualitative content analysis of the interview data was conducted to determine emerging
themes around language and approach to working with youth, service provision, and
characteristics and service needs of clients/participants.

At some agencies, multiple staff members were interviewed.

Page 33

Chapter 3

Findings from the Youth Interviews
The research team conducted interviews with 949 youth ages 13-24 in order to gain a better
understanding of the characteristics, experiences, and service needs of young people engaged
in the sex trade in the United States. Interviews took place in six sites: Atlantic City, NJ; the
Bay Area (San Francisco and Oakland), CA; Chicago, IL; Dallas, TX; Miami, FL; and Las
Vegas, NV.

The interview instrument was semi-structured, combining a range of open-ended and closedended items. The separate reports for each site provide rich details on emergent qualitative
themes and findings. This chapter presents the major quantitative findings gained from
pooling data across all six sites.

Organization of Findings
The data collection and research methodologies are described in-depth in Chapter Two. In
brief, the interviews covered the following major domains, addressed respectively in the
sections that follow (see Appendix B for the full instrument):


Demographic characteristics;



Commercial sex market involvement;



Making and spending money;



Recruitment and interactions with customers;



Involvement with “pimps” and “market facilitators” (these terms are defined below);



Health and service needs;



Interactions with the police; and



Expectations for the future.

Chapter 3. Findings from the Youth Interviews
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 34

Besides reporting overall descriptive findings, distinct themes and patterns were analyzed for
the following major subgroups:


Gender: All tables provide a breakdown for cis males, cis females, and trans females.
Totals also include the small number (6) of trans males in the sample.11



Age: The narrative draws attention to a relatively small number of significant and notable
differences between those ages 13-17 (legal minors) and 18-24, while Appendix D
provides a bulleted summary of select significant differences by age category.



Involvement with a Pimp: Results pointed to a substantial array of differences in the
market involvement, experiences, and needs of interview participants who were and were
not subject to coercion and control by a pimp (see definition below).



Other Characteristics: While these factors did not systematically or repeatedly
differentiate the sample, differences were also analyzed based on sexual orientation,
race/ethnicity, and whether the interview participant had children. The narrative draws
attention to differences that were both significant and noteworthy; Appendix D provides a
more thorough bulleted summary of subgroup differences on these factors.

Finally, for readability and because significant and meaningful differences by site were not
present across the interview instrument, pooled six-site results are generally reported. A
separate final section at the end of this chapter describes several notable areas where results
in one or several sites did, in fact, systematically differ from the rest. Also, Appendix E
shows in table form a complete breakdown of interview responses by site.

Demographic Characteristics of the Sample
Table 3.1 presents the demographic background of the interview participants. As the results
indicate, they were diverse in numerous ways. Sixty percent were cis female, 36% were cis
male, 4% were trans female, and 6 youth were trans male (less than 1%). The sampling
frame was intentionally limited to youth ages 13 through 24 (see Chapter 2), and given this
restriction, the average age was 19.3 years, with 21% (199 youth) under the age of 18.

When someone is cisgender, they identify their gender as what they were assigned at birth. For
example, someone who is cis female was assigned female at birth and identifies as female. When
someone is transgender, they identify their gender as something other than what they were
assigned at birth. For example, someone who is trans female was assigned male at birth but
whose gender identity is female.

Page 35

Table 3.1. Demographic Characteristics
Gender

Cis male

Cis female

Trans females

Total

19.7***
0%
0%
1%
5%
10%
15%
22%
13%
13%
8%
8%
5%

19.0
1%
1%
3%
7%
13%
20%
19%
11%
9%
4%
6%
5%

21.1
0%
0%
0%
0%
0%
5%
8%
29%
18%
18%
13%
8%

19.3
0%
1%
2%
6%
12%
18%
19%
13%
11%
6%
7%
6%

16%
84%

25%
75%

17%
83%

21%
79%

36%

60%

100%

57%***
27%
13%
3%

52%
42%
5%
1%

32%
21%
45%
3%

53%
36%
9%
2%

69%
14%
7%
8%
2%

70%
12%
9%
7%
3%

76%
3%
11%
3%
8%

70%
12%
8%
7%
3%

48%**
22%**
14%
8%
7%
1%

48%
30%
10%
5%
4%
4%

30%
35%
19%
11%
3%
3%

47%
27%
12%
6%
5%
3%

Age
Mean age
13
14
15
16
17
18
19
20
21
22
23
24
Age Categories
13-17 years
18-24 years
Gender
Sexual Orientation
Heterosexual
Bisexual
Gay
Other
Ethnicity
Black/African American
White
Multi-racial
Hispanic/Latino
Other
Living Situation
Family
Friends
Alone
Shelter
Homeless
Other

Page 36

Gender

Cis male

Cis female

Trans females

Education Level
Less than 6th Grade
6th-8th Grade
9th-11th Grade
12th Grade and above

0%
3%
48%
49%

0.2%
6%
49%
45%

0%
3%
38%
60%

0.1%
5%
48%
47%

US Born

97%

96%

100%

97%

20%***

37%

14%

30%

How old when first left home?
Mean for those who had left home
0
2
3
4
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
24
Still lives at home

15.2
0%
0%
0.3%
0.3%
0.3%
1%
0%
1%
1%
3%
4%
10%
10%
11%
15%
11%
10%
4%
1%
1%
0%
17%

14.7
0.2%
0.4%
0.2%
0.2%
0.2%
0.2%
1%
2%
2%
3%
6%
8%
14%
14%
14%
12%
7%
2%
1%
1%
0.2%
14%

16.4
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
6%
3%
11%
17%
39%
6%
11%
0%
0%
0%
6%

15.0
0.1%
0.2%
0.2%
0.2%
0.1%
0.3%
1%
1%
1%
3%
5%
8%
12%
13%
14%
13%
8%
3%
1%
1%
0.1%
15%

Age Left Home Categories
0-12
13-17
18-24
Still lives at home

10%*
57%
16%
17%

15%
61%
10%
14%

3%
75%
17%
6%

13%
60%
12%
15%

Have children

Total

Page 37

Gender

Cis male

Cis female

Trans females

Total

12.9
0%
0%
0%
1%
2%
1%
2%
4%
5%
9%
15%
21%
16%
10%
8%
2%
2%
1%
0.3%
0%

13.4
0.4%
0.2%
0.2%
0.2%
3%
1%
2%
2%
2%
4%
13%
20%
20%
16%
8%
5%
3%
1%
0%
0.2%

13.3
0%
3%
0%
0%
5%
0%
0%
0%
5%
8%
5%
27%
11%
8%
5%
19%
0%
3%
0%
0%

13.2
0.2%
0.2%
0.1%
0.4%
3%
1%
2%
3%
3%
6%
14%
20%
18%
13%
8%
4%
3%
1%
0.1%
0.1%

39%**
57%
4%

28%
68%
4%

27%
70%
3%

32%
64%
4%

16%***

30%

23%

24%

Age of first sex experience
Mean
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Age Categories
0-12
13-17
18-24
First sex experience was nonconsensual
±

Number non-missing data varied between 640 and 949.
+p<.10, * p<.05, ** p<.01, ***p<.001.

Page 38

As shown in Table 3.1, a little over half (53%) of all interview participants identified their
sexual orientation as heterosexual, with cis males significantly more likely than other
genders to identify as straight, cis females significantly more likely than others to identify as
bisexual, and trans females significantly more likely than others to identify as gay.
Nearly half (47%) of the sample reported living with family, and another 27% reported living
with friends. Of the remaining interview participants, 12% reported living alone, 6% reported
living in a shelter, 5% reported being homeless, and 3% reported other circumstances (living
with customer, pimp, house to house, etc.).
Over half of the sample (53%) reported less than a twelfth-grade education. Only 15% still
lived at home with their family; of those who did not, the average age of having left home
was 15.
Thirty percent of the sample had children, with cis females significantly more likely to report
having children (37%) than cis males (20%) or trans females (14%). Not surprisingly, older
youth were far more likely than younger ones to report having children (34% of those ages
18 years or older compared to 18% of those ages 13 to 17).
Nearly a third of the youth reported having their first sexual experience before the age of 13,
with cis males significantly more likely than others to report as much (39% of cis males v.
28% and 27% of cis females and trans females, respectively).
Nearly one-quarter (24%) of the sample were coded as describing their first sexual
experience as non-consensual,12 although they did not often use that term themselves; cis
females reported the highest percentage with a non-consensual first sexual experience (30%),
with significantly lower though hardly negligible percentages reported for cis males (16%)
and trans females (23%).
Finally, as shown in Table 3.1, almost all youth (97%) were born in the United States (those
who were not came at a young age), and the large majority (70%) were black/African-

“Non-consensual,” as used in this report, is not referring to the legal definition of the age of
consent at or above which a person is considered to have the legal capacity to consent to sexual
activity, but whether the young person interviewed described their experience as something they
did not want to engage in or something they were forced or coerced into doing.
12

Page 39

American. This percentage reflects disproportionate involvement as compared to the total
black population in those cities where interviews were conducted, as shown in Table 3.2.

Table 3.2. By Site Comparison of Percent Black/African American in
Interview Cities v. Percent Black/African American in Youth Interviews
Site
Atlantic City, NJ
San Francisco, CA
Oakland, CA
Miami, FL
Dallas, TX
Chicago, IL
Las Vegas, NV
* Source: U.S. Census, 2010.

% Black/AfricanAmerican in City*
38%
6%
28%
19%
25%
33%
11%

% Black/African
American in Sample
23%
47%
92%
86%
80%
57%

Commercial Sex Market Involvement
The interview instrument included a number of questions exploring the history of each young
person’s involvement in the commercial sex market and their current work environment and
experiences.

Age of Market Entry
As shown in Table 3.3, the first question in this section asked the young people at what age
they first had sex in exchange for money or some other good. On average, the age was 16,
although responses ranged widely from ages 6 to 24. Over 75% reported their age of market
entry as younger than 18.

Work Environment
Also shown in Table 3.3 (previous page), several questions went on to probe the nature of
participants’ work environment. About half reported that there were conflicts in the
neighborhoods where they worked. These conflicts often included arguments with others in
the sex trade, customers, pimps, and drug dealers, and most were related to competition and
money. Participants also frequently cited run-ins with police as a source of conflict.

Page 40

Table 3.3. Market Involvement
Gender

Cis male

Cis female

Trans female

16.04*
0.3%
0%
0.3%
0.3%
2%
1%
3%
8%
12%
14%
16%
15%
11%
8%
5%
2%
1%
1%
0%

15.56
0.4%
0%
0.4%
0.4%
1%
1%
4%
11%
16%
17%
17%
15%
10%
3%
3%
1%
1%
0.4%
0.4%

16.18
0%
3%
0%
0%
0%
3%
0%
6%
6%
12%
21%
18%
18%
9%
3%
3%
0%
0%
0%

15.8
0.3%
0.1%
0.3%
0.3%
1%
1%
4%
9%
14%
16%
17%
15%
11%
5%
4%
2%
1%
1%
0.2%

7%*
66%
28%

7%
74%
19%

6%
62%
32%

7%
70%
23%

Time in "the life"
Less than 1 year
1 year
3 years
4 years
5-9 years
10 or more years

13%
16%
37%
14%
19%
2%

10%
19%
34%
13%
23%
2%

3%
11%
32%
14%
35%
5%

11%
17%
35%
13%
22%
2%

Say there are conflicts in the neighborhood where they work

46%

47%

61%

53%

36%***

33%

54%

35%

What age first sold sex?
Mean
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Age Categories
0-12
13-17
18-24

Say any conflicts have led to physical fights

Total

Number of non-missing cases varied between 734 and 920.
+ p<.10, * p<.05, ** p<.01, ***p<.001.

Page 41

Participants were asked if any of the conflicts led to physical fights. Just over a third of
interviewees responded affirmatively. Trans females (54%) were significantly more likely to
report experiencing physical fights in the neighborhoods where they work compared to cis
females (36%) and cis males (33%). For trans females, examples of why these fights occurred
included: “They were hating on a trans-person for looking like a regular female,” and “Trans
ain’t supposed to be out there in front of the hotel, it’s regular females out there.” For other
respondents, responses included stories about customers not wanting to pay, customers trying to
force them to do things they did not want to do, and other people selling sex who thought the
respondents were stealing their customers.

Making and Spending Money
Table 3.4 presents findings related to earning and spending habits. Respondents were asked
about how much money they make from the sex trade. Seventy-five percent charged between
$013 and $200 the last time they saw a customer, with a median amount of $100. On average, cis
females reported charging significantly higher prices than cis males ($202 vs. $151). When
asked how much money they make in a week, responses ranged from $20 to $20,000. Answers
were recoded into seven categories, with the distribution shown in Table 3.4. Cis females
earned significantly more than cis males. Regarding working hours, over half the sample
reported that they worked 10 hours or fewer last week, and about a fifth worked more than 30
hours. There were no significant differences in hours worked per week by gender, but cis
females tended to earn the most from their work (e.g., 48% of cis females reported earning $600
or more per week compared to 28% of cis males and 33% of trans females).
Parents and non-parents had key differences on questions related to money and work. On
average, parents charged more the last time they saw a customer than non-parents ($255 vs.
$162). Parents also made more money per week than non-parents (the average fell in the $601$1000 category vs. $300-600, respectively).
When asked an open-ended question about the first thing they do with money, responses
showed substantial variation. Participants often gave more than one response. The top two
responses related to purchasing clothes or shoes (39% of interviewees) and food (32%). Just
over a quarter (26%) said they spend their money on rent or other bills, and the same percent

Some respondents exchanged sex for something other than money (e.g., drugs, housing).

Page 42

reported buying drugs or alcohol. The drug that participants most commonly reported
purchasing was marijuana, followed by cocaine products, heroin and other drugs.
Several significant differences were found based on gender regarding how study participants
spend their earnings. Cis males were significantly more likely to purchase drugs (25%) than the
two other gender categories (16%). Trans females (22%) were significantly more likely than the
rest of the sample (7% or fewer) to purchase cigarettes, and cis females were much more likely
than cis males and trans females to report purchasing items for children—reflecting their higher
probability of having children in the first place, as shown above.
Overall, 42% of study participants reported having another source of income, with older
participants (ages 18-24) significantly more likely than younger ones to report another source of
income (45% v. 25%). In addition, 22% of the older participants reported owing money—
oftentimes to family and friends—compared with 10% of their younger counterparts.

Obtaining Customers
Study participants were asked about where and how they find customers. As shown in Table
3.5, most participants found customers on the street, followed closely by the internet and
through friends. Nearly half (42%) reported using the internet to obtain customers. Trans
females were particularly likely to get customers from the internet (76% for trans females
compared to 45% and 37% for cis males and cis females, respectively). The most common
internet sites used were Adam4Adam, Backpage, Craigslist, and Facebook.
Participants were asked how many customers they typically saw per night/day. Responses
ranged from 0 to 20 and were generally clustered between one and five (mean = 4.6; median =
4.0).14 There were notable differences by gender, age, and sexual orientation. Trans females
reported a mean of 6.2 customers per day/night, cis females a mean of 5.0, and cis males a mean
of 3.8. Younger participants averaged seeing more customers than older participants (average of
5.4 customers for those ages 13-17 years v. 4.4 for ages 18-24).

One outlier of 250 and 11 other outliers were censored at 20.

Page 43

Table 3.4. Making and Spending Money
Gender

Cis male

How many hours did you work last week?
0 hours
1-10 hours
11-20 hours
21-30 hours
31-40 hours
More than 40 hours

Cis female

Trans female

Total

12%
44%
17%
11%
7%
9%

14%
37%
13%
13%
8%
15%

10%
32%
19%
19%
7%
13%

13%
39%
15%
12%
8%
13%

49%
33%
7%
11%
$151*
$100

39%
32%
13%
16%
$202
$115

60%
27%
7%
7%
$111
$60

43%
32%
11%
13%
$190
$100

2%***
7%
35%
28%
16%
4%
8%

1%
3%
21%
27%
24%
9%
15%

30%
37%
17%
13%
3%

1%
5%
26%
28%
21%
7%
12%

42%
37%+
27%
25%***
7%**
4%**
26%**

37%
29%
25%
16%
6%
16%
39%

47%
41%
25%
14%
22%
0%
47%

39%
32%
26%
19%
7%
11%
35%

Reports having other sources of income

42%

40%

55%

42%

Reports owing anyone money

18%

20%

26%

20%

Amount charged to last customer
< $100
$101-200
$201-$300
> $300
Mean
Median
How much do you make in a week?
$0 / No longer working
< $100
$100 - $300
$301 - $600
$601 - $1000
$1001 - $1500
> $1500
First thing you buy when paid?±±
Clothes or shoes
Food
Rent or other bills
Drugs/Alcohol
Cigarettes
Items for children
Other

Number non-missing data varied between 663 and 833.
+ p<.10, * p<.05, ** p<.01, ***p<.001.

Page 44

Table 3.5. Customers
Gender
Where do you get customers?±±
Street
Internet
Friends
Referral
Other (Parties, Casinos, Strip Clubs, etc.)
Pimp
Regulars
Average number of customers seen each day/night
0
1
2
3
4
5
6
7
8
9
10
>10
Mean
Median
How often customers from pimp?
Never
Rarely
Often
All the time
Of those who have pimp: report internet was used to get
customers
Of self-generated customers: report internet was used to get
customers

Cis male

Cis female

Trans female

Total

64%
45%***
39%
28%

66%
37%
36%
22%

71%
76%
23%
20%

63%
42%
39%
26%

16%+
4%***
2%

20%
13%
2%

8%
0%
3%

18%
9%
3%

2%
20%
20%
19%
13%
10%
5%
2%
3%
1%
1%
4%
3.7***
3

1%
14%
12%
18%
13%
13%
9%
5%
3%
2%
4%
8%
5.0
4

0%
6%
12%
12%
18%
12%
9%
6%
3%
0%
9%
12%
6.2
5

1%
16%
15%
18%
13%
12%
7%
4%
2%
2%
3%
7%
4.6
4

78%*
11%
7%
4%**

74%
11%
7%
8%

93%
5%
2%
0%

76%
11%
7%
6%

57%

39%

41%

39%***

53%

68%

46%

The number of non-missing cases varied between 271 and 900.
Multiple responses were allowed for each question.
+p<.10, * p<.05, ** p<.01, ***p<.001.
±±

Page 45

Regarding how often customers obtained customers from a pimp, 76% responded never, 11%
rarely, 7% often, and 6% all the time. Significant differences were found by gender, age, and
sexual orientation. Trans females were the least likely group to report working with a pimp
(98% answered never or rarely compared to 85% of cis females and 89% of cis males). In
addition, younger participants were modestly but significantly more likely to obtain
customers through a pimp. Specifically, 17% of those ages 13-17 compared to 12% of those
ages 18-24 reported “often” or “all the time” obtaining customers through a pimp.
The ways that people reported finding customers were not mutually exclusive: even if they
sometimes obtained customers through a pimp, it did not mean they did not other times
obtain customers on their own at parties, from the internet, etc.

Pimps and Market Facilitators
For the purposes of this report, a “pimp” is a person who exploits an individual in the sex
market through coercion, control, or force, whereas a “market facilitator” is a person who
helps obtain customers but with whom the relationship does not have a coercive, controlling,
or forceful nature.
A battery of questions were asked to allow researchers to code and clarify the role, if any,
specifically of pimps (as distinct from market facilitators) in participants’ lives. Participants
were asked whether anyone helped them obtain customers (the word “pimp” was not
explicitly used here), and if so, what their relationship was like with that person—whether
they shared money, whether there were rules and, if so, what the rules were, or whether there
was any abuse. Based on responses to multiple questions (including open-ended responses
regarding the nature of any “rules,” whose coding was reviewed by multiple researchers),
researchers liberally coded a dichotomous yes/no variable for pimp status. Liberal coding
means coding “yes” wherever participant responses left any doubt; hence, reported results
may somewhat overstate the prevalence of pimps in the sample. Researchers then created a
dichotomous variable for market facilitator status as well.

Prevalence of Pimps in the Lives of Sampled Youth
Overall, 15% of participants were classified by researchers as working with a pimp—a
slightly higher percentage than those who explicitly identified as obtaining customers from a
pimp (13% answered that they obtain customers from a “pimp” often or all the time). More

Page 46

than four in ten (42%) of the 15% of study participants who had pimps in turn responded that
the pimp had rules.15 Examples of these rules included:


Percentage of earnings between 15% and 100% returned to pimp each day;



Quota to stop working for the day, beatings for non-compliance;



Require money from customers upfront;



Rules around drug use;



Time limits with customers;



Not allowed to have partners; and



Not allowed to leave home after certain hours.

Relationship of Pimp Status and Gender
Significant differences were found in pimp involvement based on gender. Cis females (21%)
were significantly more likely than cis males (7%) and trans females (9%) to work with a
pimp. Figure 3.1 displays the gender breakdown for the entire sample, those controlled by a
pimp, and those not controlled. Whereas cis females represented 60% of the total interview
sample and 56% of those without pimp involvement, cis females represented 82% of those
with pimp involvement (cis males represented 16% and trans females 2%). Also notable, of
those with pimps, cis females (48%) and trans females (44%) were significantly more likely
to report that their pimp had rules than cis males (29%).

A respondent was coded as having a pimp if they answered that they share money with a pimp,
they have a “pimp” who helps them get customers, or they identified the person who helps them
get customers as having rules that could be determined as coercive or controlling.

Page 47

Figure 3.1 Gender Breakdown of Full Sample Compared to
those with a Pimp
90%

82%

80%
70%

60%

56%

60%
50%

39%

36%

40%
30%

16%

20%
10%

0%
Cisfemale

Cismale
% of Sample

% of Pimped

Transfemale
% of Not Pimped

Relationship of Pimp Status to Other Interview Responses
Results indicate that those involved with a pimp were more likely than others to have a first
sex experience at an extremely young age (40% v. 30% at age 12 or younger) and to have a
nonconsensual first experience (35% v. 22%). In addition, those with a pimp reported
earning more than others. Specifically, those involved with a pimp made significantly more
money per week (55% with v. 38% without a pimp made more than $600, although the
average number of daily customers was not significantly different). Those with a pimp were
also more likely to report conflicts in their neighborhoods (65% v. 51%).

Page 48

Prevalence and Nature of Market Facilitators
The results indicate that 19% of respondents had a market facilitator who was not a pimp.
The distinction between market facilitators and pimps is an important one. Both facilitate the
young people’s participation in commercial sex markets, mostly by linking them to
customers. However, the pimp exerts coercion, control, or force. Moreover, as shown in our
open-ended ethnographic data, pimps may impose strict rules on the youth, which can
include setting prices for them, requiring a percentage of their money, forcing them to do
things they do not want to do, and exerting broad control over their movements and
whereabouts. On the other hand, a market facilitator does not exert control (e.g., see Curtis et
al. 2008; Marcus et al. 2016; Wagner et al. 2016). Often the market facilitator and young
person do not necessarily share money,16 do not have no rules for interacting with each other,
and neither has to work with the other; but, both parties find the relationship to be mutually
beneficial. For example, local drug dealers may send clients to young people they know who
are exchanging sex for money. In return, if the young people have customers who are
looking for drugs, they will refer to the local drug dealers. It is one of the many ways that
different individuals in the underground economy work together. Often, as indicated in our
richer set of ethnographic data, market facilitators consist of other young people (of all
genders) who are also exchanging sex and refer customers who, for any number of reasons,
may be deemed more appropriate for a different youth. The relationships are complicated and
do not necessarily fit within any definition or stereotype. Recognition of the role that is often
played by collaborative—i.e., non-coercive—market facilitators enables a more nuanced and
accurate understanding of the complex relationships maintained by youth who trade sex.17

Legal Definition of Trafficking
The Trafficking Victims Protection Act of 2000 (TVPA) defines trafficking as the
recruitment, harboring, transportation, provision, or obtaining of a person for sex trafficking
in which a commercial sex act is induced by force, fraud, or coercion, or in which the person
induced to perform such act has not attained 18 years of age. Any child (under the age of 18)

In some cases they may provide each other with referral fees.
For example, some couples choose to work together, with one being the market facilitator and
the other exchanging sex. While the temptation may be to say that the (often) male partner is
therefore “pimping” his (often) girlfriend, the qualitative data show that one cannot force this
narrative into a “pimp” status. Young people do many things in order to survive.
17

Page 49

engaged in commercial sex is legally considered a victim of trafficking. Accordingly,
although 15% of youth in our sample were specifically involved with pimp, 32% met the
legal definition of trafficking either due to having a pimp or due to a current age under 18.
Further, 80% of youth in our sample met the legal definition of trafficking at some point in
their lives, either because they had a pimp or because they were under the age of 18 when
they first traded sex (77% were underage at the time of their initial market involvement).

Interactions with the Police
As shown in Table 3.6, while 65% of the sample had ever been arrested, only 16% had ever
been arrested for prostitution. Of those with an arrest, 82% of the charges involved
nonviolent offenses such as petty larceny, shoplifting, drugs, and trespassing/loitering. Only
11% had been arrested for prostitution in the past year. Interestingly, while no significant
difference was found in past history of any arrest, respondents with pimp involvement were
significantly more likely to report having ever been arrested for prostitution than respondents
not involved with a pimp (28% v. 13%).
Table 3.6. Interactions with the Police
Gender

Cis male

Cis female

Trans female

Total

74%***

60%

72%

65%

12%**

17%

37%

16%

Arrested for prostitution in the last year

9%**

10%

30%

11%

Ever arrested outside city of interview

20%**

14%

19%

16%

EXPERIENCE WITH POLICE
Ever arrested
Ever arrested for prostitution

±
+

Number of non-missing cases varied between 718 and 825.
p<.10, * p<.05, ** p<.01, ***p<.001.

There were also significant differences by gender. Cis males were more likely to report ever
having been arrested than cis females (74% v. 60%). By contrast, trans females (37%) were
far more likely than cis males (12%) and cis females (17%) to report ever having been
arrested for prostitution specifically; and trans females (30%) were more than three times

Page 50

more likely than either cis females or cis males to report having been arrested for prostitution
in the last year.
Regarding age, participants ages 18 and older were significantly more likely than younger
ones to report having ever been arrested (69% v. 51%); and to report having been arrested
outside of the city where the interview was held (20% v. 4%). However, there were no
significant differences in arrest for prostitution (ever or past-year) between age categories,
suggesting that the differences in “ever” arrested responses may simply reflect the longer
lifetimes and hence longer period exposed to potential arrest of those who were older at the
time of the interview.

Health and Social Service Needs
Table 3.7 presents information from study participants regarding their health problems,
social service needs, interactions with social services, and drug use.

Physical Health
A majority of study participants (64%) had seen a doctor within the last three months, and
93% reported seeing one within the last year. Most also reported having no health problems,
although some (27%) reported non sex-related physical problems such as allergies, asthma,
bipolar disorder, and vision problems. No significant differences by gender were found.
Most participants (84%) stated that they used protection against sexually transmitted
infections (STI) and pregnancy “all the time,” with 94% stating that they used protection “all
the time” or “often.” Only 3% reported using protection “rarely” or “never.”
Nearly a third (31%) of participants reported ever having an STI—most commonly
chlamydia, with significant differences by gender. Cis males were least likely (22%) to
report having an STI, whereas trans females were most likely (41%).

Social Service Participation and Needs
About half (51%) of participants reported ever having been to a social service agency for
help. Social service involvement significantly varied by gender, with trans females (71%)
most likely to have been to a social service agency followed by cis females (51%) and cis
males (48%). In addition, parents were significantly more likely than non-parents to have

Page 51

sought help from a social services agency (66% v. 44%); and parents were also significantly
more likely to seek food stamps from social services agencies (19% vs. 8%).
Of those who went to a service agency at some point, while the largest percentage of
participants reported seeking help with rent or housing, a fairly even distribution of responses
across other options shows that interview participants sought a wide range of services.
Of final note, independent of formal service participation, a majority of participants (72%)
reported having someone to talk to about their life situation if they needed help.

Drug and Alcohol Use
Nearly all participants (84%) reported using drugs or alcohol. The highest reported use was
for marijuana (66%) and alcohol (58%), with 13% reporting cocaine or crack, 7% heroin,
and 20% some other drug (often “meth” or pills). Excluding alcohol, 73% reported using at
least one type of illegal drug.
Reported drug use significantly differed by gender, with cis males (90%) and trans females
(89%) more likely than cis females (79%) to report using drugs or alcohol in general, and
with cis females also the least the least likely gender subgroup to report using each specific
drug whose results are in Table 3.7. Despite these gender differences, as the data in Table 3.7
make clear, rates of drug use were still generally high across the board, although our
questions did not allow drawing conclusions about the severity of drug dependence.

Demographic Differences by Age and Race/Ethnicity
The questions concerning health and social service usage revealed consistent differences
across both age and race/ethnicity categories. As compared to younger study participants,
older ones (ages 18-24) were significantly more likely to report problems of various kinds
but were also significantly more likely to report having a person they could talk to and
having visited a social service agency. Specifically, older participants were more likely to
report seeing a doctor in the past three months (66% v. 58%); experiencing non-sex related
physical health problems (29% v. 19%); having had a STI (34% v. 22%); having someone to talk
to (74% v. 64%); and having visited a social services agency (55% v. 36%).

Page 52

Table 3.7. Health and Needs
Gender

Cis male

Cis female

Trans female

When did you last see a doctor?
< 3 Months Ago
3-6 Months Ago
7-12 Months Ago
Over a year ago

64%
18%
9%
9%

64%
19%
11%
6%

83%
3%
3%
10%

65%
18%
10%
7%

What kind of health problems, if any, do you have?
None
Non sex-related physical
Sex-related
Mental Health-Related
Multiple

65%
31%
2%
2%
0%

65%
24%
6%
3%
3%

66%
28%
3%
3%

65%
27%
4%
2%
2%

How often do you use protection against pregnancy and STIs?
All the time
Often
Sometimes
Rarely/Never/NA

82%
12%
3%
4%

82%
12%
3%
3%

91%
6%
3%

82%
12%
3%
3%

22%***

36%

41%

31%

Have someone to talk to about life situation or when help is needed

74%+

70%

84%

72%

Ever gone to a social services agency for help

48%*

51%

71%

51%

26%*
12%
9%

17%
14%
13%

17%
7%
10%

20%
13%
12%

13%+
11%

9%
9%

21%
10%

11%
10%

90%**

79%

89%

84%

72%*
65%**
15%
6%
22%

65%
52%
12%
7%
19%

75%
64%
14%
4%
11%

66%
58%
13%
7%
20%

Ever had an STI

Service provided by social services agency
Housing or Rent
Counseling/Mental Health
Food Stamps

Total

±±

STI Treatment/Prevention/Pregnancy Testing
Food
Use any drugs or alcohol
Use any of the following drugs±±
Marijuana
Alcohol
Cocaine/Crack
Heroin
Other
±
Number non-missing data varied between 560 and 878.
±±
Multiple responses were allowed for each question.
+p<.10, * p<.05, ** p<.01, ***p<.001.
Chapter 3. Findings from the Youth Interviews

Page 53

Regarding race/ethnicity, white (66%) and multi-racial (61%) participants were more likely
than Latino (56%) and black/African-American (46%) participants to report having visited a
social service agency. White participants (20%) were also more likely than black/African
American (7%) and Hispanic (2%) participants to seek food from a shelter (p<.01). White
participants, however, were significantly less likely to report having health problems than
black/African American and Hispanic participants (51% v. 68% v. 64%, respectively).
Further, black/African Americans were significantly more likely than white participants to
report using alcohol (62% vs. 35%), whereas white participants were significantly more
likely than all other racial/ethnic groups to report using crack/cocaine, heroin, and other
drugs.

Expectations for the Future
Participants were asked about their opinions of their work, habits, and future plans. Nearly
three-fourths of participants said there was something they liked about “the life,” whereas
more than four-fifths said there was something they disliked. Sixty-two percent had tried to
leave “the life,” and 63% reported that, if they wanted to leave the life tomorrow, they would
know how—meaning, conversely, that more than one-third of the sample (37%) reported not
knowing how to exit.18
As presented above, 51% of participants reported ever going to a social service agency for
help. Shown below in Table 3.8, almost one-fifth (19%) reported having been approached by
a social services agency. Respondents were asked if there were an agency designed just to
meet their needs, what services would they want. Responses were coded into categories, with
the top three all related to basic socioeconomic and survival needs: employment/education

White study participants were far more likely to report knowing how to leave the life than
black/African American participants (83% vs. 57%). Heterosexual participants were more likely
to report having tried to leave “the life” than bisexual participants (63% vs. 58%, p<.05). Gay
participants (79%) were significantly more likely to report knowing how to leave “the life” than
heterosexuals (62%), bisexuals (61%) and other sexual orientations (33%). Gay participants
(64%) were also significantly more likely than heterosexuals (42%) to have suggested that a
social service agency help with housing/utilities.

Page 54

(49%), housing/utilities (47%), and food/money (36%). By comparison, only 12% of
respondents identified counseling or advice as what a service agency would ideally offer.
Underlining the role of unmet socioeconomic needs in youth involvement in “the life,” those
who sought an agency that could meet basic employment/education or housing/utilities needs
were also significantly more likely than others to report that they “disliked” something about
the life; that they had gone to a social service agency in the past; and that they had previously
attempted to leave the life. Despite their prior history of seeking help and actually attempting
to leave the life, at the time of the interview our data also showed that those reporting basic
survival needs (employment, education, housing, or utilities) were not more likely than
others to answer affirmatively that they would know how to leave the life tomorrow.

Table 3.8. Expectations
Number of Cases±

Cis male

Cis female

Trans female

74%
2%

72%
1%

40%
-

72%
1%

77%**
2%

87%
1%

93%
-

83%
1%

Ever tried to leave the life

57%*

65%

78%

62%

If wanted to leave the life tomorrow, would know how

66%+

60%

78%

63%

66%

60%

78%

19%

56%**

44%

63%

49%

45%+
34%
12%*

47%
37%
19%

75%
31%
6%

47%
36%
16%

Addiction Services/Healthcare/Sex Ed

12%

13%

11%

Other (Transportation, Drugs, Clothing, Etc.)

Is there anything you like about this work?
Yes
Not sure
Is there anything you dislike about this work?
Yes
Not sure

Ever approached by social service agency to offer services
If there were an agency that existed just to meet your needs
what would they offer?
Employment/Education
Housing/Utilities
Food/Money
Counseling/Advice

±
+

Total

Number of non-missing cases varied between 718 and 825.
p<.10, * p<.05, ** p<.01, ***p<.001.

Page 55

Differences by Research Site
Whereas the six research sites generally evinced a substantial degree of similarity in the
essential findings and patterns (see Appendix E), there were a number of differences meriting
explicit discussion. Most of the site-specific differences involved one or, at most, two sites
deviating significantly from the pattern found across the others on a particular item or set of
related items.
 Participant Demographics: Miami’s sample was significantly younger—on average,
17.6 years of age compared to 19.9 years for the other five sites combined. Miami
also had a significantly higher percentage of non-U.S. born interviewees (8%,
compared to 1% for the other sites combined).
 Street-Based Customer Recruitment: A significantly higher percentage of
respondents from Miami and the Bay Area reported obtaining customers on the street
(both 79%), compared to 52% for the four other sites combined.
 Pimp Involvement: The Bay Area saw a far higher percentage of young people who
work with a pimp than elsewhere (29% in Bay Area v. 12% in the other five sites
combined). This finding is consistent with previously published claims, largely based
on reported law enforcement experiences, that the prevalence of pimp-controlled
prostitution is higher in the Bay Area specifically and California generally than
elsewhere in the country (e.g., see MISSEY 2008; Sully 2013).
 Role of Market Facilitators: Atlantic City and Las Vegas stood out as having the
highest percentages of young people working with a market facilitator (36% and 24%,
respectively, compared to 15% for the other four sites combined).
 Social Service Participation: Three-quarters of the respondents from the Bay Area
reported having ever visited a social service agency for help—the highest percentage
of all sites. (The five other sites averaged 46% having visited a social service agency;
and Miami had the lowest percentage at 33%.) The Bay Area site also had the highest
percentage of young people reporting that they had been approached by a social
service agency to offer services (35% v. 19% for the other five sites combined).
Chicago had the highest percentage of youth reporting that social service agencies
should offer more help with employment and education (64%), with this emerging as
the greatest expressed need in Las Vegas (56%) and Dallas (55%) as well.
 Drug Use: Atlantic City respondents were significantly more likely to report using
cocaine/crack (43%) and heroin (35%) than other sites (9% and 4%, respectively for
combined five other sites).

Page 56

 Arrest History: Atlantic City and Dallas had the highest percentage of respondents
who had ever been arrested, both at 88%, with other sites’ percentages ranging from
55% to 70%. Atlantic City saw the highest percentage of respondents ever having
been arrested for prostitution—31% compared to 14% for the other sites combined.
Atlantic City and Dallas also had the highest percentage of respondents reporting that
they were arrested in the last year for prostitution—23% and 19%, respectively,
compared to 9% for the other four sites combined.

Page 57

Chapter 4

Findings from Official Data and
National Population Estimate
This chapter presents relevant arrest totals for all 50 states. Second, we present prosecution
and recidivism outcomes for select cities from the six in which the youth interviews were
conducted. Third, we present population estimates for the interview sites and the United
States.

Youth Prostitution Arrests Nationwide
Prostitution Arrests in All 50 States
The data in Table 4.1 provides the number of prostitution arrests in all 50 states. We obtained
state-based arrest data in 34 states for youth under the age of 18 and in 26 states for youth
ages 18 to 24 (see Table 4.1, first column). In the remaining states, we used data collected by
the Uniform Crime Reporting (UCR) program of the Federal Bureau of Investigation (see
Table 4.1, second column). Where data was obtained from both the UCR and state-based
data sources, the two figures were averaged (see Table 4.1, third column). For the slightly
older 18-24-year-old age group, the FBI does not make arrest statistics available, meaning
that information could only be obtained from state data sources (see Table 4.1, fourth
column). Major findings include:


Annual Arrest Volume: Overall, there were an estimated 1,130 arrests of underage
youth (under the age of 18) for prostitution in 2009. This figure would be exactly the
same whether relying exclusively on FBI data for all 50 states or averaging FBI and statebased data sources where numbers from both sources were available.



Concentration of Youth Arrests: Arrests were spread unevenly, with an estimated twothirds (67%) taking place in just five states: California, Nevada, New York, Texas, and
Washington. California alone accounted for 429 arrests (38% of the national total). On
the other end of the spectrum, 23 states reported fewer five or fewer arrests.



Higher Numbers of Arrests of 18-24-Year-Olds: The numbers of arrests are much
greater for the 18-24-year-old age group. In the 26 states for which data was available for
this age group, there were a total of 4,399 prostitution arrests in 2009. The arrests were

Chapter 4. Findings from Official Data and Population Estimates
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 58

also spread more widely, with only four states that reported five or fewer arrests in one
year (Delaware, Idaho, South Dakota, and West Virginia).
The UCR program yielded a nationwide number of 71,355 prostitution and commercialized vice
arrests of individuals of all ages in 2009. Since 2009, such arrests may have declined, as the
UCR program reported 47,598 such arrests in 2014. (The UCR program, however, explicitly
cautions against using its data for trend analysis.)

Limitations in Data Collection Procedures and Quality
As described in Chapter 2 and further illustrated in Table 4.1, this project revealed flaws in
the data collection and reporting of underage prostitution arrests nationwide. Although UCR
data could be obtained for all 50 states, only 34 of 50 states provided data on underage
prostitution arrests from valid state-based data sources. Those states that did provide data
sometimes provided imprecise numbers (e.g., combining prostitution, exploitation, and
solicitation charges under a single category, which might lead prostitution arrests to be
overestimated, or potentially lacking complete data on arrests handled in juvenile court,
which might lead prostitution arrests to be underestimated). Further, regardless of the
underlying state penal laws, UCR data universally combines numbers into a “prostitution and
commercialized vice” category, which potentially combines prostitution, exploitation, and
solicitation arrests, rather than isolating prostitution. In addition, given the relatively low
charge severity of prostitution offenses, law enforcement agencies are not necessarily
required to report, nor do they necessarily report, all prostitution arrests to the UCR program,
leading to other potential inaccuracies.
The cumulative effect of these data limitations are illustrated in observed discrepancies
between the state-based and UCR numbers in 15 of 34 states where both data sources
provided numbers, as shown in the first two columns of Table 4.1. Discrepancies also existed
in ten of the 14 states where at least one of the data sources reported an arrest total greater
than five arrests. Accordingly, the data collection process itself underlined important
limitations in reporting and understanding the scope of the criminal justice response to young
people in the sex trade in the United States.

Page 59

Table 4.1. Prostitution Arrests by Age
Under 18
State*
Alabama1
Alaska1
Arizona1
Arkansas1
California
Colorado
Connecticut1
Delaware2
Florida
Georgia
Hawaii2
Idaho1
Illinois
Indiana
Iowa1
Kansas
Kentucky1
Louisiana1
Maine1
Maryland1
Massachusetts1
Michigan
Minnesota
Mississippi
Missouri1
Montana
Nebraska1
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota1
Ohio
Oklahoma
Oregon
Pennsylvania1
Rhode Island2
South Carolina
South Dakota
Tennessee2

State

FBI

Average of
State and FBI

0
2

0
2
28
0
429
13
0
0
51
48
4
0
41
11
2
0
1
10
0
23
5
7
30
8
3
0
2
76
0
16
2
15
11
0
10
8
26
9
1
2
1
19

0
2
28
0
429
13
0
0
31
48
4.5
0
34
11
2
0
1
10
0.5
23
5
7
30
8
2.5
0
2
76
0
13
2
52.5
7.5
0
10
8
14.5
9
0.5
2
0.5
18

0
0
11
5
0
27

1
1
23
5
7
30
0
0
2

10
2
90
4
0

3
9
0
0
17

Ages 18-24
State Data
Sources
134
58
21

11
5
408
124
2
559

82
7
241
133
133
244

15
1,167
70

102
258

1
467

Page 60

Table 4.1. Prostitution Arrests by Age
Under 18
State*
Texas
Utah1
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming1
Total

State

FBI

Average of
State and FBI

96
0

124
24
1
1
57
0
9
0
1,130

110
12
1
1
92.5
0
9
0
1,130

1
128
0
0
474

Ages 18-24
State Data
Sources
1,436

29
406
0

4,399

Note: Data collected as part of the Uniform Crime Reporting (UCR) program of the
Federal Bureau of Investigation (FBI) are for Prostitution and Commercialized Vice, a
category that includes the “unlawful promotion of or participation in sexual activities for
profit, including attempts,” a definition potentially encompassing prostitution, solicitation,
and exploitation offenses. Whereas it is likely that few underage individuals were arrested
on solicitation or exploitation charges, it cannot be ruled out that in some states, the UCR
data slightly overestimates arrests specifically for prostitution.
* Data for Washington, DC was not collected.
1
State-based data utilized the UCR charge categories, meaning that the numbers reflect
prostitution and commercialized vice.
2
State-based data combined prostitution and solicitation for prostitution charges (but does
not include exploitation-related charges).

Sex and Race Distribution of Nationwide Prostitution Arrests
For those states that provided data, the data in Table 4.2 indicates that approximately four in
five arrests for prostitution were of female defendants (81% for under 18 arrestees and 78%
for 18-24-year-olds). The data also indicates that over half of the arrestees under the age of
18 are black (55%), and 43% of 18-24-year-olds are black. Most of the remaining defendants
were white. Notably, data was not available for transgender defendants.

Table 4.2. Percent of Arrests by Gender and Race (2009)
Demographics
Gender*
Female
Male
Race
Black
White
Other

Under 18

18-24

81%
19%

78%
22%

55%
35%
8%

43%
52%
5%

* Transgender not reported.

Page 61

Arrests on Exploitation or Promoting Prostitution Charges
From 11 states, we were also able to collect aggregate data on the number of arrests of
exploiters (assisting or promoting prostitution) in 2009. Table 4.3 presents the total number
of arrests made on such charges in those states, as well as a breakdown by gender (with data
transgender defendants not available). In all states but one, more men were arrested for
exploitation crimes, except in North Carolina. Overall, 35% of those facing exploitation
charges were women, and 65% were men.

Table 4.3. Exploitation Arrests (2009)
State

Total Arrests

Male

Female

Hawaii
Michigan1
New Mexico
North
Carolina1
Oregon
Rhode Island
South
Carolina2
Tennessee
Virginia1
Washington
West Virginia1
Total

25
53
20

20
40
17

5
13
3

149

98
20

80
-

18
-

11
96
77
35
607

10
59
59
20
382

1
37
18
15
205

1
2

NIBRS code: Assisting or Promoting Prostitution
Combined codes Pimping and Hire/Enter House of Prostitution

Prostitution Case Processing in the Youth
Interview Sites
Arrest Numbers in the Interview Sites
As shown in Table 4.4, in 2009, the five interview sites for which such data could be
obtained combined for 1,907 prostitution arrests of individuals under the age of 25. Across

Page 62

these sites, 455 individuals under the age of 25 were arrested in San Francisco;19 321 in
Chicago; 540 in Dallas; 408 in Las Vegas; and 183 in Miami.
Data on underage prostitution arrests (under the age of 18) could only be obtained for three
sites and indicates that there were 17 such arrests in Chicago (representing 5.3% of all under
25 prostitution arrests in Chicago), 34 arrests in Dallas (representing 6.3% of under 25
prostitution arrests), and one in Miami.
The bottom section of Table 4.4 shows the percentage of arrests in each state that came from
our interview sites. Across four sites for which data was available, from 35% to 55% of
under 25 prostitution arrests came from our interview sites, which in most cases were the
largest cities in the state.

Background Characteristics
Table 4.5 presents the background characteristics of youth arrested for prostitution (under
age 25) in 2009 in five of the interview sites (unavailable for Atlantic City). The mean age
rounded to 20 or 21 years old in all sites and, when narrowing to the underage population
(13-17-year-olds), the mean age was 16 or 17 years old. The majority of those arrested were
female in Chicago, Dallas and Las Vegas. In San Francisco and Miami, the under 25
population arrested for prostitution was more than four in ten male (41% in San Francisco
and 46% in Miami). San Francisco and Miami also deviated from the other three sites in
racial composition. Specifically, the percentage of black arrestees was lower in San
Francisco and Miami than in the other sites. Contrasting with the other sites, 42% of
arrestees in Miami were Hispanic, and 18% in San Francisco were Asian.
The criminal history information that we were able to obtain for four sites indicates that the
population of interest has sizable involvement with the criminal justice system, with an
average of 7.1 prior arrests in Las Vegas, 6.4 in Chicago, 4.0 in Miami and 2.7 in Dallas. The
prior criminal history data refers to any charge, not exclusively prostitution.

Neither aggregate nor case-level data for the combined Bay Area, including Oakland, could be
obtained from state or county data sources.
Chapter 4. Findings from Official Data and Population Estimates
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 63

Table 4.4. Number of Youth/Young Adults Arrested on Prostitution Charges in 2009 by Age
Interview Site

AGE AT TIME OF ARREST
13 years
14 years
15 years
16 years
17 years
18 years
19 years
20 years
21 years
22 years
23 years
24 years
Ages 13-17 Years
Ages 13-18 Years
Total (Younger than Age 25)
Statewide Totals

San
Francisco1

Chicago

100%

1
2
3
0
11
31
50
45
52
47
47
32
17
48
321

0%
1%
1%
0%
3%
10%
16%
14%
16%
15%
15%
10%
5%
15%
100%

0
0
5
6
23
53
71
82
74
81
64
81
34
87
540

0%
0%
1%
1%
4%
10%
13%
15%
14%
15%
12%
15%
6%
16%
100%

455

California

PERCENT OF STATE ARRESTS
FROM INTERVIEW SITE
Ages 12-17 Years
Ages 12-18 Years
Total (Younger than Age 25)

Las Vegas2

Dallas

Illinois

Texas

63%
56%
55%

35%
38%
35%

18
55
75
85
82
93
0
0
408

Miami3

4%
13%
18%
21%
20%
23%
0%
0%
100%

0
0
0
0
1
13
22
22
40
24
28
33
1
14
183

0%
0%
0%
0%
1%
7%
12%
12%
22%
13%
15%
18%
1%
8%
100%

Nevada

Florida

54%

9%
41%
44%

Aggregate data from San Francisco obtained for 18-24-year-olds. Statewide data from California not available.
We were not able to obtain juvenile data (18 or younger) from Nevada.
3
Numbers come from all of Miami-Dale County, Florida.
2

Table 4.5. Background Characteristics for Youth/Young Adults Arrested for
Prostitution in 2009 (Younger than Age 25)
Interview Site
Number of Individuals
DEMOGRAPHICS
Mean Age
Mean Age (13-17 years)
Mean Age (13-18 years)
Sex
Female
Male
Race/ethnicity
Black
White
Hispanic
Asian or other race/ethnicity
Born in the United States of America

San
Francisco

Chicago

Dallas

Las
Vegas1

Miami

455

321

540

408

183

20.1

20.7
16.0
17.3

20.9
16.5
17.4

21.9

21.4
17.0
17.9

59%
41%

92%
8%

87%
13%

97%
3%

54%
46%

32%
48%
-18%
--

53%
45%
2%
0%
97%

57%
42%
-1%
91%

45%
50%
-6%
93%

22%
36%
42%
1%
84%

6.4
70%

2.7
72%

7.1
74%

4.0
56%

CRIMINAL HISTORY
Average Number of Prior Arrests
Any Prior Arrest
Note: Due to rounding, percentages do not always add up to 100%.
1
Mean age figures are for 18-24 In Las Vegas.

Case Outcomes
Table 4.6 provides information on the case outcomes in prostitution cases in 2009 for youth
under age 25 in five sites (excluding Atlantic City, and with limited information in San
Francisco and Las Vegas). As shown in Table 4.6, the percentage of cases ending in a
conviction ranged from 28% in Miami to just under 60% in the three other sites represented
(Chicago, Dallas, and Las Vegas). In three of the sites, Chicago, Dallas and Miami, data
enabled isolating the underage age group (13-17-year-olds). Results indicated that the
younger age group was convicted less often than 18-24-year-olds (7% vs. 21%, results not
shown). In Las Vegas, the conviction rate was similar regardless of age category.

Chapter 4. Official Data and Population Estimate
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 65

Table 4.6. Case Outcomes for Youth Prostitution Arrests in 2009 (Younger than Age 25)
Interview Site

Chicago

Dallas

Las Vegas

Miami

Number of Cases
Number of Cases Ending in Conviction
Number of Cases Ending in Jail or Prison

176
101
73

755
573
556

770
454

353
205
80

DISPOSITION TYPE
Pled Guilty/Convicted
Dismissed
Deferred Prosecution Agreement
Declined to Prosecute
Pre-Trial Diversion

58%
7%
35%
---

56%
27%
18%
---

59%
41%
----

28%
2%
8%
60%
2%

SENTENCE TYPE (If Convicted)
Jail
Time Served
Conditional Discharge
Fine
Other

73%
6%
8%
2%
10%

97%
----97%
6%

39%
---27%1

DAYS OF INCARCERATION
Average Days Sentenced to Jail
All Cases
Cases Ending in Conviction
Cases Ending in Jail

28.7
75.8
88.3

42.2
61.4
63.3

18.1
64.9
97.5

Note: Due to rounding, percentages do not always add up to 100%.
In Chicago, data was obtained on 404 cases pending a disposition, leading to an N of 176. In addition, of the 808 arrests in Dallas, 53
were pending as of when data was received, leading to an N of 755.
-- indicates field was not provided.
1
In Miami, 27% of defendants received community supervision, generally probation.

Page 66

Of those convicted, in three sites where sentencing data was available, a high percentage
received a jail sentence. Specifically, 97% of cases received both a jail sentence and fine in
Dallas, 73% received jail in Chicago, and 39% received jail in Miami. Of those cases that
were sentenced to jail, defendants received on average a two-month jail sentence in Dallas
and approximately a three-month jail sentence in Chicago and Miami. When isolating the
younger age group (13-17-year-olds), we found that only in Chicago was this younger age
group given a shorter jail sentence than 18-24-year-olds.

Re-Arrest Rates
Table 4.7 presents re-arrest rates for the four sites that could provide reliable recidivism data
(for the under 25 population). Two years after the initial prostitution arrest, 36% of youth in
Las Vegas, 42% in Miami, 46% in Dallas, and 64% in Chicago were re-arrested on any
charge. Notably, in the two sites for which prostitution re-arrests could be distinguished, such
arrests accounted for well under half of all re-arrests on any charge. In Chicago, the sample
averaged 1.33 re-arrests on any charge compared to 0.54 prostitution re-arrests over two
years; and in Dallas, the sample averaged 1.02 re-arrests on any charge compared to 0.37
prostitution re-arrests. These findings further confirm the pattern detected in the youth
interviews (see Chapter 3), with most arrests of the prostitution-involved population not
specifically involving prostitution charges per se.
Table 4.7. Recidivism Among Youth/Young Adults Arrested on Prostitution Charges in 2008
Interview Site

Chicago

Dallas

Las Vegas

Miami

Number of Individuals in Recidivism Sample

332

357

152

One Year After Initial Arrest
Any Re-Arrest
Number of Re-Arrests
Any Prostitution Re-Arrest
Number of Prostitution Re-Arrests

54%
0.67
21%
0.21

29%
0.51
11%
0.16

13%
0.15
---

18%
0.56
---

Two Years After Initial Arrest
Any Re-Arrest
Number of Re-Arrests
Any Prostitution Re-Arrest
Number of Prostitution Re-Arrests

64%
1.33
33%
0.54

46%
1.02
22%
0.37

36%
0.41
---

42%
1.57
---

Page 67

Case Processing of Exploitation Cases
Background Characteristics and Case Outcomes
Table 4.8 presents information regarding individuals arrested on sexual exploitation of
children charges in five of the interview sites (excluding Atlantic City). The results generally
do not point to a consistent cross-site profile of these individuals. They were on average
approximately 30 years old (ranging from 25.0 years in San Francisco to 32.8 years in
Miami). The percentage who were male ranged from 60% to 71% in four of the five sites and
was 96% in Las Vegas. In regards to race, those arrested on exploitation charges were 80%
black in San Francisco, whereas the other sites showed a more mixed breakdown of white
and black individuals—along with 30% Hispanic in Miami. Those arrested also had
significant prior experience with the criminal justice system, with the number of prior arrests
on any charge varying from 4.1 in Las Vegas to 4.8 in Dallas to 6.8 in Miami.
In regards to the initial exploitation offense, the conviction rate across the five sites ranged
from a low of 12% in Las Vegas to a high of 55% in Miami. Prison and jail were used as a
common sentence type in cases of a conviction. Jail was imposed in 67% of cases in
Chicago; either prison or jail were imposed in 95% of cases in Dallas (where sentences
almost always included a fine as well); and prison or jail were imposed in 69% of cases in
Miami. Dallas sentenced those convicted of sexual exploitation offenses, on average, to five
years in prison, whereas jail or prison lengths were significant lower in the other sites, as
shown in Table 4.8.

Recidivism
Re-arrest data could be obtained from four of the six sites for individuals initially arrested on
an exploitation charge. After a two-year tracking period, the re-arrest rate on any charge was
9% in Las Vegas, 36% in Chicago, 39% in Dallas, and 50% in Miami. (Available data did
not enable isolating re-arrests on exploitation charges specifically.)

Page 68

Table 4.8. Background Characteristics and Case Outcomes for Individuals Arrested for
Commercial Sexual Exploitation of Children in 2009
Interview Site

San Francisco Chicago Dallas

Number of Cases

Las
Vegas

Miami

132

25.0

30.8

30.5

31.2

32.8

40%
60%

38%
62%

30%
71%

4%
96%

31%
69%

80%
17%
-2%
--

45%
48%
--7%
78%

56%
43%
--2%
90%

67%
30%
-3%
72%

29%
41%
30%
0%
71%

4.8
87%

4.1
62%

6.8
57%

43%
0%
57%
---

43%
20%
37%
---

12%
87%
-0%

55%
17%
17%
11%

SENTENCE TYPE (If Convicted)
Prison
Jail
Straight Probation
Conditional Discharge
Fine

0%
67%
--33%
---

50%
45%
5%
--95%

6%
63%
5%
-----

INCARCERATION AND SUPERVISION
Average Days Sentenced to Jail or Prison
All Cases
Cases Ending in Conviction
Cases Ending in Jail or Prison Sentence

43.0
50.6
60.0

685.7
1,991.8
1,991.8

46.4
84.2
122.5

DEMOGRAPHICS
Mean Age
Sex
Female
Male
Race/ethnicity
Black
White
Hispanic
Asian or other race/ethnicity
Born in the United States of America
CRIMINAL HISTORY
Average Number of Prior Arrests
Any Prior Arrest
DISPOSITION TYPE
Pled Guilty/Convicted
Dismissed
Adjournment in Contemplation of Dismissal
Declined to Prosecute

31%
69%
---

Note: Due to rounding, percentages do not always add up to 100%. Criminal history data was not obtained from San
Francisco or Chicago. Sentencing information was not obtained from San Francisco and Las Vegas. Note that 22 individuals
did not have a final disposition in Chicago, they were coded as bond forfeiture and not included in this analysis.
-- indicates a field that was not provided.

Page 69

Table 4.9. Recidivism Among Individuals Arrested on Commercial Sexual Exploitation of
Children Charges in 2008
Interview Site

Chicago

Dallas

Las Vegas

Miami

One Year After Initial Arrest
Any Re-Arrest
Number of Re-Arrests

32%
0.52

19%
0.45

6%
0.06

33%
1.06

Two Years After Initial Arrest
Any Re-Arrest
Number of Re-Arrests

36%
0.92

39%
1.00

9%
0.09

50%
2.01

Number of Cases in Recidivism Sample

Population Estimates
We calculated a range of estimates for the number of underage youth in the United States
engaged in the sex trade (see Chapter 2 for the methodology underlying these estimates).
Table 4.10 presents the findings. Based on available official data sources, there were 1,130
arrests of individuals under the age of 18 on prostitution charges in 2009. Given this number,
and based on estimated percentages of the full population of interest that experiences a
prostitution arrest in a given year (determined through the youth interview data), the most
likely range of underage youth in the sex trade in the U.S. falls between 8,915 and 10,507.
Recognizing the data limitations described in Chapter 2, we also created a wider range of
estimates, respectively based on a bare minimum plausible percent of the population with a
past year prostitution arrest (5.38%, or half of 10.75%) and a maximum plausible percent
with a past year prostitution arrest (25.34%, or double 12.67%). When applying these
assumptions, the results indicate that the true population falls between a minimum of 4,457
(if we assume a 25.34% annual arrest rate) and 20,994 (if we assume that 5.38% of the actual
population is arrested in any given year).

Page 70

Table 4.10 Population Estimates Based on Official Prostitution Arrest Data for Underage Youth (Under 18 Years of Age)

State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire

State Data:
Prostitution
Arrests of
Under 18
Youth in 2009
0
2
0

0
0
11
5
0
27

1
1
23
5
7
30
0
0
2

FBI Data:
Prostitution
Arrests of
Under 18
Youth in 2009
0
2
28
0
429
13
0
0
51
48
4
0
41
11
2
0
1
10
0
23
5
7
30
8
3
0
2
76
0

Average = ∑
(Official Number of
Prostitution Arrests
of Under 18 Youth
in 2009)
0
2
28
0
429
13
0
0
31
48
4.5
0
34
11
2
0
1
10
0.5
23
5
7
30
8
1.5
0
2
76
0

Population
Estimate
Using
10.75%
0.00
18.60
260.47
0.00
3,990.70
120.93
0.00
0.00
288.37
446.51
41.86
0.00
316.28
102.33
18.60
0.00
9.30
93.02
4.65
213.95
46.51
65.12
279.07
74.42
13.95
0.00
18.60
706.98
0.00

Population
Estimate
Using
12.67%
0.00
15.79
220.99
0.00
3,385.95
102.60
0.00
0.00
244.67
378.85
35.52
0.00
268.35
86.82
15.79
0.00
7.89
78.93
3.95
181.53
39.46
55.25
236.78
63.14
11.84
0.00
15.79
599.84
0.00

Population
Estimate
Using
5.38%
0.00
37.17
520.45
0.00
7,973.98
241.64
0.00
0.00
576.21
892.19
83.64
0.00
631.97
204.46
37.17
0.00
18.59
185.87
9.29
427.51
92.94
130.11
557.62
148.70
27.88
0.00
37.17
1,412.64
0.00

Population
Estimate
Using
25.34%
0.00
7.89
110.50
0.00
1,692.98
51.30
0.00
0.00
122.34
189.42
17.76
0.00
134.18
43.41
7.89
0.00
3.95
39.46
1.97
90.77
19.73
27.62
118.39
31.57
5.92
0.00
7.89
299.92
0.00

Table 4.10 Population Estimates Based on Official Prostitution Arrest Data for Underage Youth (Under 18 Years of Age)

State
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
TOTAL 50 STATES

FBI Data:
Prostitution
Arrests of
Under 18
Youth in 2009
16
2
15
11
0
10
8
26
9
1
2
1
19
124
24
1
1
57
0
9
0

Average = ∑
(Official Number of
Prostitution Arrests
of Under 18 Youth
in 2009)
13
2
52.5
7.5
0
10
8
14.5
9
0.5
2
0.5
18
110
12
1
1
92.5
0
9
0

Population
Estimate
Using
10.75%
120.93
18.60
488.37
69.77
0.00
93.02
74.42
134.88
83.72
4.65
18.60
4.65
167.44
1,023.26
111.63
9.30
9.30
860.47
0.00
83.72
0.00

Population
Estimate
Using
12.67%
102.60
15.79
414.36
59.19
0.00
78.93
63.14
114.44
71.03
3.95
15.79
3.95
142.07
868.19
94.71
7.89
7.89
730.07
0.00
71.03
0.00

Population
Estimate
Using
5.38%
241.64
37.17
975.84
139.41
0.00
185.87
148.70
269.52
167.29
9.29
37.17
9.29
334.57
2,044.61
223.05
18.59
18.59
1,719.33
0.00
167.29
0.00

Population
Estimate
Using
25.34%
51.30
7.89
207.18
29.60
0.00
39.46
31.57
57.22
35.52
1.97
7.89
1.97
71.03
434.10
47.36
3.95
3.95
365.04
0.00
35.52
0.00

474

1,130

10,507

8,915

20,994

4,457

State Data:
Prostitution
Arrests of
Under 18
Youth in 2009
10
2
90
4
0

3
9
0
0
17
96
0
1
128
0

* No data was available for Washington, D.C. Numbers for the third column were computed as the average of the first two columns—an average of the state-based
data source and FBI data source—wherever both data sources were populated. The 50-state total of 1,130 appears in both the second and third columns (for FBI
data and for the average obtained from both data sources, but those numbers are identical by coincidence; the results are based on different state-by-state
computations. The final totals for all 50 states are rounded (no decimals).

Chapter 5

Perspectives of Social Service
Providers and Law Enforcement
In four of the sites where youth interviews took place (Atlantic City, Bay Area, Miami,
Chicago), the research team identified and interviewed staff at 18 social service and law
enforcement agencies.20 In some cases, these providers worked with the young people
specifically because of their involvement in the commercial sex industry, but in many cases
their interactions were based on some other aspect of the youth’s identity or experience.
The interviews were semi-structured, and their purpose was threefold: 1) to learn the exact
locations of tracts, hotels, beaches, etc. to inform outreach for the youth interviews; 2) to
understand the types of available service organizations, the services offered, and the
challenges to service provision; and 3) to learn, from the view of social service providers and
police officers, about some of the common characteristics, experiences, and needs of the
youth.

Types of Social Service Organizations and
Services Offered
There are different types of social service organizations that work with youth involved in the
commercial sex market, and the 18 in this study represent that range. In most cases, the
programming of these agencies was not geared exclusively to youth in the sex trade,
although there were a few whose name and mission had “sexual exploitation” or “sexually
exploited youth” in it. Organizations with specific programming for sexually exploited youth
reported that referrals most often come from police officers and other law enforcement
officials, juvenile courts, and district attorney’s offices.
Many of the organizations we interviewed were working with youth because of some other
aspect of their identity or experience: foster care involvement, homelessness, LGBT

At some agencies, multiple staff members were interviewed.

Chapter 5. Perspectives of Social Service Providers and Law Enforcement
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 73

community member, or juvenile justice system involvement. We interviewed staff from
youth homeless shelters, LGBT centers, youth empowerment organizations, agencies that
work with victims of physical and sexual abuse, substance abuse treatment groups, and
policy advocacy organizations.
Many of the organizations offered a variety of services, although they tended to fall into the
following categories: counseling, support groups, case management, job assistance, parenting
classes, and legal and educational advocacy. The youth shelters usually did not have these
services, but instead offered food, a place to stay, clothing, bus passes, and hygiene kits, and
often held life skills groups, LGBT support groups, and yoga classes. At one of the shelters, a
staff member stated that 30% percent of the youth who stayed there were transgender, and
that the shelter was the only safe place for them. Staff from the LGBT center we interviewed
said they took a harm reduction approach, focusing their activities on safer sex, HIV
prevention, and encouraging the youth to make sure they tell someone where they are at all
times; staff at this agency did not try to get the youth out of the sex trade.
Some organizations provided additional services. One interviewee stated that they provide
young people with smart phones “because otherwise kids will trade sex for those things,” and
another stated that they provide “care free activities” such as art and jewelry making—
“things that aren’t so intense or heavy.” One organization that works with girls coming out of
the juvenile justice system stated that they do not have programming specifically for women
in the sex trade, as “they all heal the same way, and isolating the issue doesn’t help—these
women do not want to be defined by their offense.”

Youth Involved in the Commercial Sex Market
Social service providers differed in the characteristics they identified of the youth in the sex
trade, and this often varied by type of organization. For instance, staff from organizations
whose mission it was to work with sexually-exploited females perceived that most of the
youth in the sex trade were females exploited by a pimp. Staff from organizations whose
mission was anything other than sexual exploitation were more likely to perceive that the
population was equally divided among males and females; staff from two organizations also
highlighted the prevalence of exchanging sex for money among transwomen. One advocate
stated that the sex trade is something that both males and females are involved in, although
females tend to be targeted or identified by law enforcement.

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The youth these organizations encountered were mostly English speaking, and many were
from the foster care system. Staff from a few organizations said that over half were involved
in foster care, and staff from another organization stated that 70% of them had previous
contact with the local Department of Children and Families. In Miami, in part because yearround warm weather makes it a destination for homeless youth, interviewees talked about the
prevalence of runaways in the sex trade. Similarly, in Atlantic City, the interviewees stated
that the sex market was seasonal, and that during the warmer months there were a lot of
runaways from other states who “turn to survival sex on the streets.”
The social services staff who were interviewed agreed on some characteristics: involvement
in the sex trade was equally prevalent across race, many of the involved youth faced family
issues such as abuse and neglect (and corresponding self-esteem problems), and most faced
economic hardship. Some also identified that many youth come from single parent homes
with lots of children, and others identified past sexual abuse or parental criminal justice
histories as common among this population. Issues of poverty were overwhelmingly
identified by staff from every organization. Youth had basic needs such as housing and food.
Many were eligible for supplemental security income (SSI) but were not receiving it.

LGBT Youth
Those who worked with the LGBT population stated that a significant percentage of gay
youth are kicked out of their homes because of their sexual orientation; many of these young
people wind up on the street. One interviewee stated that gay male youth often exchange sex
with older men for places to stay. For trans females in particular, one interviewee stated:
The transgender population is definitely involved in the sex work industry. For trans
female youth, there is a lot of social pressure to do this work, and it is almost a rite of
passage for them to “really be trans.” There are not many places for them to go and
find community, so they go to the sex clubs, and there’s an expectation that they’ll
also go to the Tenderloin and sell their bodies. It’s really hard for trans kids to get
jobs because there’s so much prejudice against them, so finding someone to employ
you is really challenging. When you’re young, the jobs available to you are things like
CVS or McDonald’s. Those places have an endless pool of unskilled labor; they won’t
hire the trans kid. In doing sex work, they can make a lot of money quickly and save
enough to get their surgery.

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Market Entry
There was no consensus among social service organizations about how youth entered the
market. Some stated that girls were often recruited by other girls, moms, and, for runaways,
by people at bus stops. Some stated that girls are recruited by their boyfriend/pimp. Others
stated that it is a mix: some are recruited by friends, some are forced, and some are entering
the life on their own. One stated that there was family pressure to do it—their fathers are
pimps and their mothers are prostitutes. Finally, others stated that it is very easy to get
involved, and many just find their own way into the market and do not work with anybody.
As one interviewee stated, “To try to find a way in which you can’t fall into [commercial sex
work] is way harder than finding ways in which you can.” Another made a similar point by
stating, “Hustling is a ‘safer’ way to make money [than other underground economic
activities] because the charges are usually loitering and it’s not a felony.” Staff from multiple
organizations emphasized that many youth do not believe they are doing anything wrong
because “it’s so normal” in their worlds, and in some cases, girls were pressuring their male
friends to help them facilitate their interactions with customers.

Language and Framing
Some interesting tensions arose in the interviews around vocabulary. Some organizations
used the term “commercial sexual exploitation of children,” or “CSEC.” For those who used
CSEC, they most often used the word “girls” when referring to the population, reflecting
their belief that all or most of the CSEC population was female. These organizations were
also more likely to use the word “victim” when discussing youth in the sex trade.
Other staff took issue with the “CSEC” and “girls” language, with one interviewee stating,
“Exploitation language triggers people.” Another saying, “Young people don’t necessarily
see themselves as exploited,” and that people should not be defined by their offense.
Several interviewees highlighted that the narrative that most of the youth in the sex trade
were girls was problematic: “There are lots of boys doing it too.” As one interviewee stated:
What about boys? When we talk about this in public, we talk about girls, and the men
who buy sex from them. The movement hasn’t been engaged in services for LGBTQ
individuals.

Page 76

When referring to females, others stated that they purposely say “young women” instead of
“girls.” Instead of “CSEC,” many organizations used “youth engaged in survival sex.” One
interviewee from a homeless shelter defined survival sex as “trading sex for money, drugs, or
housing.” Another from a different shelter—one designed specifically to work with sexually
exploited females—called survival sex a “bullshit term.” At one LGBT center, staff said they
use the language of the youth: “sex work,” “hookin’ and crookin’,” “hustling,” or “other
job.”
There was also tension around the terms “victims” and “trafficking.” One interviewee stated
that, “We need to push back on the language. People say foreigners are trafficked and
domestics are engaged in prostitution. Call it all human trafficking, they are all victims.”
Another stated that it was “crazy” to label all youth engaged in the commercial sex market as
being trafficked. Staff at one agency felt that labeling the youth as victims takes away their
agency, and that the goal of working with the youth should not be to “rescue” them, but to
support them in making their own decisions.
Another tension around framing arose on the topic of pimps. Staff at one organization stated
that all girls have some sort of pimp, but boys do not have pimps. Another organization’s
staff said that it is hard to believe that most are not pimped and controlled in some way.
Other organizations said that there was a mix—some had pimps, others had friends who
helped them get customers but were not pimps, and that some were what they called
“renegades,” engaging in the commercial sex market completely on their own. One
interviewee stated that many do it on their own: “Girls have been pimping themselves
because it gives them power.” Another stated that the idea of a “pimp” is complicated, and
reducing the conversation to pimp as perpetrator and youth as victim is unhelpful, especially
when the “pimp” is also a youth growing up facing issues of poverty:
While the girls didn’t necessarily choose this life, the pimps didn’t necessarily choose
it either, and many of them are young men from the same family situations, and they
were groomed just like the girls were, just for a different role. But nobody is talking
about them as needing help, they are just thought of as criminals.
Finally, social service providers had different perspectives about police. According to one
interviewee, “The police see [youth] as offenders, the court sees them as victims.” Many felt
that law enforcement officials have changed their attitudes over the years. As one stated,
“Some police still say things like ‘a hoe is a hoe,’ but even the roughest are starting to

Page 77

change their attitudes and have the youth’s best interests in mind because they are kids.” One
advocate said that, “Law enforcement mistakenly thinks all girls have pimps,” and one police
officer said that the goal is “to rescue victims, prosecute pimps.” One officer referred to
transgender youth as “crossdressers,” indicating that is still a need for training and education
regarding appropriate language and understanding.

Challenges
When asked about the challenges of working with youth in the sex trade, responses fell into
four main categories: the field, the police, logistics, and the youth.

The Field
There is growing media and policy attention on the issue of youth involved in the
commercial sex market. A “field” has emerged—one where government and private funders
sought to fund programs, criminal justice agencies sought to create new practices and
policies, and researchers sought to generate knowledge. However, indicated through the
service provider and law enforcement interviews, conflicts exist over language and framing
of the problem. These conflicts are heightened by the realities of limited funding, leading
agencies to try to differentiate their programming or approach to the issue. One interviewee
stated that “everyone is facing funding issues,” while another across the country explained:
For service providers, there is territorialism around money. Every provider thinks
they have the answer for these young people, so they are essentially competing with
each other for funding, claiming they have the best program.
Another provider stated:
Providers are confusing their own survival with what’s best for the kids. It creates an
identity that you have to follow. Their hearts are good, but they are too worried about
funding and job security than really serving their population with an open mind.
The need to secure funding often requires agencies to create singular narratives that can
exclude many youth in the sex trade, often limiting programming and discourse, for example,
to a focus on girls.

Page 78

Some interviewees mentioned that articulating the problem is part of the problem. The
framing of the field as “anti-trafficking” comes up against “anti-prostitution” statutes, which
leads to confusion on the part of the police and court system. Additionally, according to one
police officer interviewed, when the word “trafficking” is used, money and resources often
go to foreign human trafficking, not domestic. This sentiment was echoed by a service
provider in another city: “Historically, trafficking programs worked with international folks
only.” Nearly all of the interviewees stated that there are not enough resources to address
domestic trafficking.
One interviewee who works with girls in the juvenile justice system stated that some young
people see the framing of “commercial sexual exploitation of children” (“CSEC”) or
“trafficked” as problematic.
Girls in juvenile hall see programs for CSEC youth and they get angry, because what
about them? There are no services for them, but they face the same issues and
challenges as CSEC girls. Just chose a different way to hustle. Some chose to sell
drugs because they were uncomfortable selling their body, but they’re labeled
criminals while others are labeled victims.
Finally, one police officer interviewed discussed the need for certain narratives—i.e., young
girls being forced, coerced, and controlled—to frame the dominant discourse in order to
convince politicians to pass laws like the New York Safe Harbor Act. He stated that it would
be impossible to convince white, male state senators to pass a law that does not criminalize
youth in the sex trade if you tell them that boys are involved or that many of the female
youth are choosing to do this. This is problematic, however, because discourse shapes
funding and programming, and it is precisely the narratives that, in the accounts we heard,
maximize funding opportunities that ignores the majority of the population of youth who
exchange sex, as shown in Chapter 3.

The Police
Across the different sites in this study, the police were identified by service providers as a
challenge. The service providers do not believe that arresting the young people is helpful.
Even when the policy in certain cities is not to arrest, it is still happening. One interviewee
stated, “The official stance of criminal justice agencies is that [the youth are] victims, but

Page 79

they still arrest. Police are arresting because they feel it’s the safest thing to do.” Another
interviewee explained:
Police are stuck on the idea that the only way to keep the kids safe is to arrest them
and put them in juvenile hall. So even though they say they see them as victims,
they’re still arresting them. And they arrest them more if they get attitude … What’s
most lacking is a coordinated response and an awareness of roles. Providers focus on
the youth and protecting them, and the [police department] is mostly charging the
girls with loitering, solicitation, disturbing the peace, or having no identification …
The [police department] needs written protocols to respond to, and they don’t have
that, so there’s no system in place for when they pick up a youth to do anything but
arrest them.
In another city that does have a law to protect this population from arrest, a service provider
stated, “Cops are still arresting kids though. Not usually for prostitution but for drugs.”
Another service provider stated that the district attorney, prosecutors, and police say one
thing, but it does not trickle down to the beat officers, and that there is no “system in place to
immediately provide intervention when they are arrested … they’re just going through the
revolving door of the criminal justice system.”
Finally, one interviewee stated that, “too many of these girls are being locked up for the
purposes of prosecution of the pimps and because there is nowhere else to put them.” In
another site, a service provider stated something similar: “There is a safe house, but it’s used
only for girls who are ready to testify against their pimp. But what about the rest of the
people who aren’t pimped or looking to testify?”
Across the wide range of types of social service providers and approaches to working with
youth who exchange sex, a clear consensus emerged from those we interviewed that the
police arresting these young people was a serious problem.

Logistics
Some interviewees identified resources as a challenge to serving this population.
Specifically, agencies lacked sufficient staffing to meet the needs of the population. Service
providers indicated that more staff is needed for outreach, as well as for direct service. One
interviewee stated that, “We get a lot of referrals but don’t have the staff to address them

Page 80

all.” Another said, “It’s hard working with CSEC youth, and we are lacking in people to do
it. It’s intense, one-on-one, and it takes a long time.” Finally, transportation was an issue—
“the kids know how to get around but don’t have the money to do it.”

The Youth
Across the sites, service providers identified the youth themselves as a challenge, for
multiple reasons. One interviewee stated that, “The nature of being a teen makes it difficult
to serve them. It’s hard to maintain contact, there are scheduling conflicts, kids lose their
phone or run out of minutes.” Another provider stated that the youth will open up about most
things in their life, but do not want to discuss their involvement in the commercial sex
industry for fear of being judged or because they do not want people in their community to
find out. Some providers felt that it was hard to offer an appealing alternative to “the life,”
when they could not provide the youth with money or jobs that paid as much as they could
make by exchanging sex. One interviewee stated that she often hears the girls she works with
say things like, “I can’t get a regular job because I’ll have to wait two weeks to get paid,
when I can get $40 right now.”

What the Youth Need
Housing
When asked about what the youth need in order to exit “the life,” nearly everyone
interviewed identified the top need as safe housing—a lack of which makes the youth
vulnerable to entry or continued presence in the sex market. Additionally, the housing “must
feel like a home.” Many of the youth are escaping abusive families or foster homes or live in
overcrowded apartments. One staff member summarized housing issues LGBT youth face:
Many LGBT youth don’t have places to live because they aren’t accepted at home
because of their sexual orientation. At the shelters, LGBT kids don’t always feel
comfortable there because the social workers are very focused on family
reunification, and these young people do not want to go back home or into foster
care.
Some stated that safer foster homes, independent living programs, stable family
environments, and group homes that are trauma-informed were all needed.

Page 81

Other Youth Needs
Other needs that were commonly identified by social service staff included:


Counseling;



Other mental health and healing services;



Job readiness/training;



Actual jobs;



Education support;



Targeted case management;



Legal advocacy;



Cell phones;



Bus passes;



Substance abuse services; and



Self-sufficiency skills to avoid co-dependency (relationships, drugs).

There was not necessarily agreement on the list above, although all were stated by multiple
interviewees. For example, while nearly all stated that the youth needed counseling, two
interviewees did not think that counseling was a primary need. As one stated:
They don’t necessarily need counseling. Counseling pathologizes the young people,
and they wouldn’t need as much of it if they had housing, stability, and selfsufficiency skills.
As shown in Chapter 3, only 12% of youth respondents stated that if there were a social
service agency designed to meet their needs, counseling was a service they would want.
Instead, housing and education/employment were the top two services identified by the
youth.

Page 82

Social Service Agency Needs
Finally, some staff identified things social service agencies need to better serve this
population. These needs included more bilingual staff, more staff education around trauma in
the juvenile justice system, and more engagement with youth on what is best for them.
Additionally, it may be that some programming does not resonate with the youth. As one
interviewee stated, “It’s adultism. We think we know better because we’re adults but we
probably don’t know their life as well as they do so we don’t know what’s best.” Another
summed up this sentiment by saying:
The girls have to be a part of the plan, we can’t force our plan for them on them …
There absolutely needs to be a client-centered response. Just because they’re kids,
don’t act like you know what’s best for them; rather, support them in healthy
decision-making.

Page 83

Chapter 6

Conclusions
The goal of this study was to increase scientific knowledge concerning the characteristics,
needs, size, and criminal justice experiences of the population of youth engaged in the sex
trade in the United States. Specifically, we sought to:


Provide a rich qualitative and quantitative portrait of the characteristics, experiences, and
health and social service needs of youth who exchange sex for money or other goods;



Analyze arrest patterns and prosecution and recidivism outcomes for these youth when
they encounter the juvenile or criminal justice systems;



Document the types of services that are available to this population; and



Estimate the size of the national population of underage youth involved in the sex trade.

Based on interviews with 949 youth ages 13-24, interviews with staff from 18 social service
and law enforcement agencies, and analysis of official records data, this study revealed
findings with implications for policy, practice, and future research.

Major Study Findings
Characteristics of Youth Involved in Trading Sex
Gender: Our study confirms prior research (Curtis et al. 2008; Dank et al. 2015) that a
substantial portion of the population involved in exchanging sex for money is not cis female.
As shown in Chapter 3, 36% of the youth we interviewed were cis male, and another 4%
were trans female. Many social services are targeting their resources to cis females and
framing their conceptualizations of the population in terms of “girls” and “young women,”
potentially making it more difficult for the approximately four in ten youth who do not fall
into the cis female category to receive assistance. In light of this study and other recent
research, there is a need for funders and policymakers to support services for the full
population of youth engaged in the sex trade, for instance through more deliberately funding
agencies whose services are not limited to one gender or, given that many cis female-

Chapter 6. Conclusions
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 84

oriented programs already exist, through funding programs that are designed specifically to
meet the needs of cis males or trans females.
Trans Youth: Transgender youth face particular challenges. As shown in Chapter 3, they
were significantly less likely than cis female or cis male youth to live with family; more
likely than other genders to report vulnerability to harassment and violence; and far more
likely to report ever having been arrested for prostitution. Research shows that when they are
in custody, transgender individuals face disproportionate risks. In a study by the Bureau of
Justice Statistics (Beck 2014), 40% of transgender prison inmates and 27% of transgender
jail inmates reported unwanted sexual activity with other inmates or sexual activity with
other prison staff members (which, by law, is considered nonconsensual)—ten times higher
than for the general prison and jail populations. Few social service providers who specifically
seek to help youth in the sex trade are addressing the unique needs of trans youth. The
discrimination trans youth often face—from their families, law enforcement, service
providers, and potential employers—makes them particularly vulnerable to entry into the
commercial sex market.
Underage v. Older Youth: Although 21% of the youth we interviewed were between the
ages of 13 and 17, there were few significant differences found between these youth and the
18- to 24-year-olds who composed the remainder of the interview sample. Additionally, the
average age when interview participants first traded sex was 15.8 years old. These findings
retroactively justified our decision to include 18-24-year-olds in the study. Our findings
suggest that young people have broadly common characteristics before and after the
“underage” cut-off, with the exception of having children (see “Children” below). These
findings suggest a need for programs and policies that extend to young adults ages 18 to 24,
most of whom have been “in the life” for a period of time extending back to when they were,
originally, underage.
Race/Ethnicity: Study findings suggest that the youth population engaged in the sex trade
is disproportionately black/African-American as compared to the larger population in each of
the six research sites. More than two-thirds of interview participants (70%) were
black/African-American. These findings mirror research on other topics regarding the greater
collective disadvantages and disproportionate justice system involvement of minority youth,
African Americans in particular, as compared to non-minority individuals.

Page 85

Childhood Trauma: Consistent with previous literature, many youth in our interview
sample appeared to have experienced childhood trauma. Social service providers identified
past sexual abuse as common in the population, and indeed, nearly a quarter of the youth we
interviewed described their first sexual experience as nonconsensual. Social service
providers also reported that foster care involvement was common, and that many youth were
runaways. On average, the youth in our sample reported first leaving home when 15.0 years
old, and they also identified housing as their most pressing need. These findings underline
the need for targeted prevention programs (perhaps anchored at a foster care agency, for
example) that are for young people who have experienced early childhood trauma, to cut off
the pathways from abuse to involvement in the commercial sex market.
Pimp Involvement: Similar to estimates in earlier studies (Dank et al. 2015, Curtis et al.
2008, Decker et al. 2012), our study found that 15% of youth in the sex trade were working
with a pimp—a person who controls their involvement in the market by the use of force,
fraud, or coercion. Pimp involvement was greatest among cis females, yet was still little
more than one-fifth of any gender (21% for cis females as compared to 9% for trans females
and 7% for cis males). As has often been the case, focusing public debate and programming
on pimped cis girls may exclude nearly 80% of the cis female population and an even higher
percentage of all youth —many of whom still have substantial and consequential needs that
pose a real barrier to exiting the life.
Children: Nearly a third of the youth interviewed in our study had children, including 37%
of cis females. Those who were parents reported working significantly more hours in the last
week than those who were not parents, and they also made significantly more money per
week than non-parents. In one of relatively few differences between the under 18 and the 1824-year-old subgroups, those ages 18-24 were significantly more likely than underage youth
to have children.
Physical Health: Overall, the youth in our sample reported some healthy behaviors: 93%
had visited a doctor in the past year, with 83% having had visited a doctor in the last six
months; only 4% reported having sex-related health problems; 82% reported using protection
against pregnancy and STIs “all the time,” and an additional 12% said “often”; and 72%
reported having someone to talk to if they needed help.
Arrests: Although the number of youth under the age of 18 arrested for prostitution
nationwide is low according to official records and our youth interviews (e.g., totaling an

Page 86

estimated 1,130 arrests in 2009), the service providers we interviewed stated that these young
people are still getting arrested—perhaps for other things such as drugs or having no
identification. Indeed, though only 16% of the youth we interviewed had ever been arrested
for prostitution, 65% had ever been arrested for any offense. Of those with an arrest, 82% of
the charges involved nonviolent offenses such as petty larceny, shoplifting, drugs, and
trespassing/loitering.
Drugs: The use of drugs among our sample of youth was high. Seventy-three percent of the
youth we interviewed reported using at least one type of illegal drug (with marijuana
overwhelmingly the most common, though by no means the only drug found in the sample).
Further, when drugs are involved, there is greater law enforcement involvement: Nearly
three-quarters (73%) of those reporting that they use marijuana, cocaine, heroin, or some
other illegal drug reported having ever been arrested, compared to 47% of all others.

Needs of Youth
Housing: Overwhelmingly, both the youth and the service providers we interviewed
identified housing as the most important type of assistance. Retention in treatment and other
services may be difficult unless stable housing is also provided. Housing must be safe—a
broad term that encapsulates many things, including: trans and gender non-conforming youth
should feel they will not be harassed; space should not be given only to those who are willing
to testify against an exploiter; and the focus of corresponding services should not necessarily
be on family reunification, given that many of these youth are leaving their family homes
because of abuse or discrimination.
Other Needs: Youth identified their top three desired forms of assistance as related to basic
socioeconomic and survival needs: employment/education, housing/utilities, and
food/money. Only 12% answered that counseling is what they most wanted—highlighting a
disconnect between what youth say they need and what social service agencies often focus
on. These findings speak to the value of youth input into the programming designed to assist
them. Given the likelihood of childhood trauma among many youth, the value of evidencebased therapeutic interventions should not be discounted; however, the data suggests that
basic survival needs may be an initial precondition and first step in an effective system of
interventions.

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Population Estimate
A precise population estimate is impossible because of the flaws in officially collected data
and the challenges to achieving an RDS probability sample, as well as major limitations in
the precision of the youth interview data in estimating the percentage of the underage
population of interest that is arrested v. not arrested in a given year. Despite the limitations
outlined in Chapter 2, we believe that the range of youth ages 13-17 in the sex trade in the
United States is likely between 8,914 and 10,507. Nonetheless, recognizing the sizable
limitations in the estimation methodology in the present study, we also report a wider range
of 4,457 to 20,995. Although the extent of this range is perhaps unsatisfying, it represents a
prudent final set of findings, given substantial unknowns that persist about the population.

Official Records Data
The Poor State of Official Records: This study revealed fundamental flaws in the data
collection and reporting of arrests for prostitution at the state and federal levels. In only 34 of
50 states did the designated Statistical Analysis Center (SAC) for each state or some other
state-based data source provide the number of underage prostitution arrests. Further, those
states that did provide data sometimes provided imprecise data for an array of reasons (e.g.,
combining prostitution, exploitation, and solicitation charges under a single penal law
category). Although FBI data obtained as part of the Uniform Crime Reporting (UCR)
program was available for every state, given the low charge severity of prostitution offenses,
law enforcement agencies are not necessarily required to report, nor do they necessarily
report, all prostitution arrests to the FBI. Furthermore, UCR data reporting categories
combines state-level charges into an overarching “Prostitution and Commercialized Vice”
category that includes prostitution, solicitation, and exploitation—even for states that have
the ability to distinguish these offenses in their penal codes. Some of the aforementioned
problems are underlined by the discrepancies between state-based numbers and the FBI
numbers in states where both data sources provided numbers (see Table 4.1 in Chapter 4).
These data discrepancies and limitations reflect an important problem. If this is a topic of
concern for policymakers at the local, state, and federal levels, better data collection
procedures and more accurate youth identification, data collection, and labeling should be
put in place.

Page 88

Strengths and Limitations of the Youth Interview Methodology
Strengths: Although there were significant limitations (discussed in depth in Chapter 2),
this study’s use of ethnographic methods and respondent-driven sampling (RDS) gave us
access to a largely hidden population. Of the youth we interviewed, 42% used the internet to
obtain customers, and only 51% reported ever having been to a social service agency for
help. Research that only recruits from social service providers or from traditional outreach
may miss large portions of the population who may be disconnected or who may not be
visible on the street. A combined strategy of using trained ethnographers and respondentdriven sampling can help access this population.
Limitations: Our methodology did not work as intended in multiple sites. In some areas
with more sprawl (e.g., Dallas), populations may not be closely networked, and RDS relies
on those networks to access its sample. In addition, to the extent that there is a coerced and
controlled indoor population of youth in the sex trade—i.e., a more tightly controlled
population than those we accessed who reported pimp involvement—we were not able to
access such a population through our study. Therefore, we cannot make claims about the
characteristics and needs of those who have that experience.

Poverty and the Underground Economy
Although policymakers, service providers, and funders at times use a “commercial sexual
exploitation of children” framework to describe youth in the sex trade, this term does not
encompass all of the youth who participated in our research. The needs expressed by the
youth themselves often related to issues of poverty and economic hardship—the need for
employment, education, housing, food, and money. The youth talked about the first things
they buy when they get paid, and these things often related to fulfilling basic needs—food,
clothing, and shelter—linked to economic survival.
Framing the Issue: Given the above, social service agencies, funders, and policymakers
may benefit from reconsidering the language and framing with regard to youth in the sex
trade, given the problematic and isolating nature of parts of the current discourse. The
labeling of youth as “exploited,” “trafficked,” or “victimized” has both positive and negative
consequences. It clearly has helped drive public and political attention to young people in the
sex trade. On the other hand, it does not always reflect the experiences of all youth, or how
the young people involved think of themselves. Related, the public discussion of trafficking

Page 89

may serve, unintentionally, to focus greater attention on those who have crossed national
borders as opposed to youth born in the U.S. Our study suggests that many youth are
involved in the sex trade as a matter of survival in the face of trauma, family dysfunction,
poverty, and discrimination. Many of the youth we talked to do indeed have chosen “this
life” from among the limited options available to them. For a large majority of the youth, the
limitations are both personal and structural, including poverty and discrimination based on
race, gender, or sexual orientation. These structures limit access to the legitimate economy,
thereby limiting the choices that young people who face them can make. Moreover, the
intersection of many of these structures—e.g., being transgender, black, and poor—makes
some people particularly vulnerable. Many end up in the underground economy, of which
trading sex is a part.
Complex Relationships in the Underground Economy: The complexity of the social
relationships among the population of youth in the sex trade is important to understand. Like
any economy or market, there are those who facilitate market transactions. In our study, we
uncovered the complexity of the relationships between youth and market facilitators, the
majority of whom are not pimps in the traditional sense of the word—people who exploit
through the use of force, fraud, or coercion. Rather, many players in the underground
economy often work together in mutually beneficial relationships to help each other survive.
For example, those who deal drugs refer their customers to the youth, and the youth refer
their customers to the drug dealers. Young people pay others to help protect them while they
work. In Las Vegas and Atlantic City—two places that are known for illegal economic
activities—the rate of having a market facilitator was higher than in any of the other youth
interview sites.

Future Research
There is much room for future research.
Pathways into “The Life”: A high percentage of the youth in our sample experienced
early childhood trauma, which may play a role in their entry into “the life.” Future research
may want to further investigate how trauma such as foster care involvement, sexual abuse,
and discrimination based on sexual orientation may lead youth into the sex trade.

Page 90

Pathways out of “The Life”: More research is needed on youth who have gotten out, to
gain a better understanding of the external circumstances and support that helped facilitate
their exit, as well as internal characteristics that empowered the youth to leave.
Program Evaluation: Few rigorous evaluations exist of programs designed specifically to
work with youth in the sex market. There is a particular need for evaluation research focused
on interventions intended to link youth with supportive housing. Such evaluations might test
whether, over the long-term, housing interventions increase the chances that youth exit the
life at a younger age, increase their likelihood of future legal employment, and increase their
future earnings.
Language: Given that the interviews we conducted were limited to English and Spanish,
future research should expand their capacity to interview in other languages, perhaps
bringing access to additional parts of the population that may not have been born in the
United States.
Older Ages: In general, with the notable exception that older youth are more likely to be
parents, this study did not detect sizable differences in the needs, characteristics, and
experiences of underage individuals (ages 13-17) and slightly older young persons (ages 1824). Yet, this study was ultimately limited to youth, broadly defined in light of
developmental research suggesting that a young person’s brain continues to develop to
approximately age 25. It is unknown to what extent the experience of the youth population
comprising the focus of the present study mirrors or diverges from individuals who remain
involved in the commercial sex market as older adults.

Page 91

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Appendix A. Youth Interviews Consent
Form
Commercial Sexual Exploitation of Children (CSEC) Study, Chicago Site
Assent Narrative and Consent Form
A.

PURPOSE OF THE STUDY

You are invited to help us do a study of teenagers who engage in sex for money in Chicagoland
area. The information I will give you can help you make a good choice about joining or not
joining the study. We hope that the information we collect will help solve some of the problems
that you and others in your situation face, and ensure that these problems become smaller and not
bigger.
You are invited to be part of this study because you said you have had sex for money and you
said you are older than 13. This study - sponsored by the federal government through a grant to
a nonprofit organization called the Center for Court Innovation in New York City. The Center
for Court Innovation hired researchers and college professors from the Chicago area to lead the
project here.
B.

PROCEDURES

If you agree to take part, you will participate in an interview that takes roughly 45 minutes. It
will ask you questions about prostituted teenagers in the Chicagoland area. We would like to
audio record some of your answers so that we can remember your exact words later. Your name
will not be used at any time during this study and you do not need to tell us your name or
show us any identification at any time. This study is completely confidential. You may
refuse to answer any questions at any time for any reason or not be recorded. If you refuse to
answer a question or do not want to participate any further, you will not be penalized in any way.
Do you agree to be recorded? Please circle either yes or no.
YES – I AGREE TO BE RECORDED _____
NO – I DO NOT WANT TO BE RECORDED _____

Appendix A. Youth Interviews Consent Form
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 98

Since we are interested in interviewing people like yourself who know about teens who have sex
for money, after your interview, we will explain how you can help us recruit other people to
participate in the study. If you should choose to help us recruit other people we will keep a
temporary record of your physical appearance – height, weight, etc., in order to insure that you,
and not somebody scamming you, are the one who receives payment. You have the option to be
interviewed in a public place that is comfortable to you, such as a coffee shop, park, McDonalds,
bus station, etc. If you prefer a more private office space, we will search for appropriate space to
accommodate this request. If you decide to participate in the interview, and later on decide that
you want to end your participation at any point, you will not be penalized in any way. If you
don’t want to talk to us, you can stop at any time.
C.

RISKS

Because of the topic of this study, there are more than minimal risks to participating. The
interview may cause you some stress or bring up upsetting things you experienced in the past.
Remember, you are free to not answer any questions or stop the interview at any time, but our
staff is prepared to help you in any way they can. All the answers you give will be kept private
and confidential. They will not be given to the police or anyone else.
D.

BENEFITS

The primary benefit is that this study seeks information in order to help professionals learn more
about how to better deal with the challenges that you and others like you face. It is hoped that
through greater knowledge about such lives, better services can be provided. In addition, many
people feel good about getting the chance to tell their story. There are no direct benefits to you to
participate in this interview.
E.

COMPENSATION

To account for your time in answering questions, we will pay you $40 at the end of the
interview, regardless of your age, ethnicity or ability to speak English fluently.
If you agree to participate in helping the project recruit three additional people to interview, you
will be paid $10 for each eligible person that you recruit who completes the interview.

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PERSONS TO CONTACT

If you have any questions about your participation in this study, you may call the Chicagoland
area study leader, Dr. Laurie Schaffner at (773) 750-9091.
If you have questions about your rights as a study participant or if you feel that you have been
harmed, contact the Center for Court Innovation’s Institutional Review Board chair in New York
City at 646-386-4183.
G.

PRIVACY STATEMENT

Your participation in this study is entirely confidential. Only a pseudonym (a fake name you
pick) will be attached to your responses. No one except the research staff will have access to
anything you tell us. The report on our findings will not be written in a way that would let
someone who reads it figure out who you are. Please choose a pseudonym now and write it on
the line below.
_______________________________________
While your responses are confidential, there is a very slight chance that an unauthorized person
may get access to them. To prevent this from happening, you will not be asked to give your
name or the names of persons you know to any member of the study team. Any answers that you
give us on surveys or in interviews will be kept in a locked file cabinet at the study office, to
which only specific study staff will have access.
H.

VOLUNTARY PARTICIPATION AND WITHDRAWAL STATEMENT

This study is VOLUNTARY. You are not giving up any legal claims or rights because of your
participation in this study. If you do join, you are free to quit at any time.
I.

AGREEMENT

Do you understand the information that we have given you and are you willing to be in this
study? If so, please write your pseudonym on the line below.
________________________________________________

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Appendix B. Youth Interview
Instrument
Interview Protocol
Thanks for volunteering to talk to me. The questions I'll ask you are about who
you are and where you live; what you do and whom you know; your financial
and health concerns; your experience with the police; and lastly I'll ask you
about your expectations.
Coupon Number:

Interviewer Name:

Interview Date:

Location:

Respondent Information
1.How old are you:

2.Date of birth(mm/dd/yyyy):

3.Country of birth:
4.State of birth:

5.City of birth:

6.Gender:
Female,

7.What is your sexual orientation:

Male,

Trans(F to M),

Trans(M to F)

Bisexual,

Heterosexual,

Homosexual,

Other

8.What is your race or ethnicity?
Asian/Pacific Islander,
Other:

Black/African-American,

Hispanic/Latino, Multi-Racial,

Native American/Alaskan Native,

White,

N/A,

Note: DO NOT ask but observe for the next 5
questions

9.Color of hair:

10.Color of skin:

11.Color of eyes:

White, Light Brown, Medium Brown, Dark
Brown, Darker, Other:

Black, Blue,Brown, Green,Hazel, Light brown,
Other:

Black, Blond(e), Brown, Grey, Red, Shaved,
Other:

Appendix B. Youth Interview Instrument
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 101

12.Height:

13.Estimated weight:

Below 5'4'', 5'5''- 5'7'',
Over 6'5'', N/A

5'8''-5'10',

5'11''-6'1'',

6'2''-6'4'',

14.Where are you from originally
(neighborhood/block affiliation):

100 – 125, 126 – 145, 146 – 165, 166 - 185, 186 – 205, 206
– 225, 226 – 235, Above 236, N/A, Other:

15.What is the highest grade you completed
in school:
5 6, 7, 8, 9, 10, 11, 12, Some College, N/A, Other:

16.What's the name of your last school:

17.When did you last go there:
N/A, This week, 1 week ago , 2 wks ago, 3 wks ago, 1 month
ago,
2 months ago, 3 months ago, 4 months ago, 5 months ago, 6
months ago,
1 year ago, 2 years ago, 3 years ago, Other:

18.What grade were/ are you in:

19.How long have you been in the life (or,

N/A, 5, 6, 7, 8, 9, 10, 11, 12, Some College,
Other:

how long have you exchanged sex for things like
money, food, shelter, etc.):

20.What neighborhood/area do you
currently live in:

21.Who do you live with:

22.How long have you lived there:

23.Who pays the rent:

24.How many places have you lived in the
last year:

25.Do you have any children: Yes,

1-2,

3-5,

6-8,

9-11,

> 12,

Boyfriend, Co-worker, Family, Foster care family, Friends,
Girlfriend, Pimp, Self, Shelter, Spouse, Streets, Transitional
housing, Other:

Other:

26.If yes, how many children do you have:

27.If yes, what ages are of your children:

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, Other:

28.Who takes care of your children:

29.How old were you when you first left your
family home, if you left:
9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, N/A,
Still live there

30.What year was that:

31.What adults lived there:

32.What is the highest level of schooling any 33.When was your first experience with sex :
of your parents completed:

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Some HS , HS Graduate, Some College, BA/BS,
Some Graduate, Graduate, I don’t know, N/A,
Other:

7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
19, Other:

34.Who was it with:

35.Can you tell me about it:

Making and Spending Money
The questions I'm going to ask you next will focus on making and spending
money
36.How old were you when you first had
had sex in exchange for something:

37.Tell me about it(what happened):

7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
19, Other:

38.Do you work on or off the streets these
days:

39.Who negotiates prices with the
customers:

40.What prices are charged:

41.How much, on average, do you charge
each time that you see a customer(probe for
different prices/different activities):

42.What did you charge the last time that
you saw a customer:

43.How much do you make in a week:

44.Do you share your money with anyone
after you get it:

45.If yes, with who and how much do you
share:

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46.What's the first thing that you buy/pay
when you get money(clothes, food, rent,
etc):

47.What other sources of income do you
have:

48.How much are your main expenses per week:

49.Do you owe anyone money:

50.If yes, who do you owe:

Yes,

51.If yes, how much do you owe:

52.If yes, for what do you owe:

53.How are you supposed to pay the money back:

Market Involvement
Now I am going to ask you some questions about where and when you work
54.Where do you usually work (tracks, areas):

55.Do you ever work, or have you ever worked in other areas (different neighborhoods,
cities, states, etc.):
Yes,

56.If yes, where:

57.What determines where you work and whether you change locations (police,
competition, pimp, events, etc.):

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Why do you change it around?

58.Where else have you worked besides the track:

59.What days/nights did you work last
week:

60.How many total hours did you work last
week:
1-10,

11-20,

21-30,

31-40,

>40

61.Are there ever conflicts in the neighborhood(s) where you work (boyfriends, residents,
store owners, dealers/gangsters, cops, customers, etc)? Tell me about some of them:

62.What have the conflicts been over (work, competition, money, etc):

63.Have any of these conflicts led to physical fights/altercations:

64.What do you do to avoid fights or violence:

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65.Are there places, like neighborhoods, certain corners or areas, that you avoid? if so
why:

66.How do you avoid these places:

67.What happens when you can’t avoid these places:

Customers
Next, I'm going to ask you about the people you come in contact with
68.Where do you get customers or dates:
Friends,

Internet,

Pimp,

Referral,

Street,

Other:

69.Which internet sites, if any, do you/your pimp use to get customers:
Adam4Adam, Blackplanet, Craig’s list, Facebook, MySpace, Vampirefreaks, N/A, Other:

70.How many customers did you see the last time that you worked:

71.How many customers do you see, on average, each day/night:

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72.Where do you go with customers:
Bars, Brothel/Parlor, Car, Client’s residence, Hotels, Own room, Parks/Alleys, Other:

73.What are your customers professions:
Business Owner/Manager,
Lawyer,
Maintenance Worker,
Politician, Postal

Bartender/Restaurant,

Mechanic,

Worker/Messenger, Sales,

Counselor,

Nonprofit/Social Service,

Construction Worker,

Doctor,

Finance,

Police Officer/Corrections Officer,

Singer/Dancer/Actor, Teacher/Professor,

Other (please specify):

74.Which neighborhoods are your customers usually from:

75.Customers ages:
10-25,

26-35, 36-45, 46-55,

56-65, 66-75,

>76,

N/A

76.Customers marital status:
Divorced, I don't know, Married, Separated, Single, Widow, Widower, Other:

77.Customers' ethnicities:
Asian/Pacific Islander, Black/African-American, Hispanic/Latino, Multi-Racial, Native American/Alaskan
Native, White, N/A

78.Is there anything else that you think we might find useful or interesting about your
customers:

79.How often do you get customers from a pimp/sponsor/market facilitator:
All the time, Never, Often, Rarely, N/A

80.Of these (pimp-generated) customers, how often are things set up through an Internet
site like craigslist:
All the time, Never, Often, Rarely, N/A

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81.Of these (pimp-generated) customers, how often are things set up through someone
approaching someone else on streets:
All the time, Never, Often, Rarely, N/A

82.How often do you get customers on your own:
All the time, Never, Often, Rarely, N/A

83.Of these (self-generated) customers, how often are things set up through craigslist or
another Internet site:
All the time, Never, Often, Rarely, N/A

84.Of these (self-generated) customers, how often are things set up through someone
approaching someone else on streets:
All the time, Never, Often, Rarely, N/A

85.Of these (self-generated) customers, how often are things set up through a
friend/referral (e.g. calling you on the telephone):
All the time, Never, Often, Rarely, N/A

86.What other ways do you get customers:

87.Over the past year, about how many customers would you say you worked with:

88.Of all these customers, how many would you say are steadies/regulars:

89.How often do you see the steadies:

90.How much do the steadies pay you:

91.Do your steadies pay you with anything besides money:

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Pimps
Now I will ask you some questions about coworkers or people who help you
find customers
92.Do you have someone who helps you to
get customers:
Yes,

93.If yes, who is (s)he:

94.How did you get to know this person:

95.How do you feel about this person:

96.How is this person important to you:

97.How do you get along with this person:

98.Does this person have rules:

Yes,

99.If yes, what are the rules:

100.(If applicable) How many others work for her/him(your pimp):

101.(If applicable) How does everyone get along(probe for respect, relationships, structure,
etc):

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102.(If applicable) Have you worked with anyone else besides the current person (pimp):
Yes,

103.Do you know any (other) pimps:

Yes,

104.What are their street names:

Network
Now I am going to ask you some questions that will better enable us to make
population estimates and understand how different types of people in the life
share networks, sort of like mapping people's friendships on Facebook. We
will be doing this by collecting the last three digits of cellphone numbers to
see who knows who. Since we do not take real names and we only ask for the
last three digits, there is no way to identify anybody and we cannot obtain
their phone number. This is purely to help the mathematicians on the project
to count population.
105.About how many teens do you know under the age of 18 that have sex for money in
this city:

106.How many are girls:

107.How many are boys:

108.How many are transgenders:

109.How many are White:

110.How many are Black:

111.How many are Asian:

112.How many are Hispanic:

113.How many are multi racial:

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114.How many are Native American:

115.Please pull out your cell phone:
Yes,

116.What are the last three digits of your cell phone number:

117.Please take a look at your cell phone and tell me how many phone numbers you have
for people under 18 who exchange sex for money:

118.How many phone numbers do you have for people under age 18 who DO NOT
exchange sex for money/commercial purposes:

119.We would like to get the last 3 digits of the cell phone numbers for people under 18
who exchange sex for money:

#1
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#2
1.What is the last 3 digits of this person's cell phone number:

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2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#3
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#4
1.What is the last 3 digits of this person's cell phone number:

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2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#5
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#6
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

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5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#7
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18,

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

N/A

Yes,
No
Other:

7.Others:

#8
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

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3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#9
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,
3.Gender:

Family,

Friend,

None of above

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#10
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

Page 115

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#11
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#12
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

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3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#13
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
22, 23, N/A

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

Yes,
No
Other:

7.Others:

#14
1.What is the last 3 digits of this person's cell phone number:
2.This person is: Associate, Coworker,

Family,

Friend,

None of above

Page 117

3.Gender:

4.Age:

Female, Male, Trans(F to M), Trans(M to F), N/A

9, 10, 11, 12, 13, 14, 15, 16, 17, 18,

5.Race-Ethnicity:

6.Does this person work for your pimp?

Asian/Pacific Islander, Black/African-American,
Hispanic/Latino, Multi-Racial,
Native American/Alaskan Native,

White,

N/A,

N/A

Yes,
No
Other:

7.Others:

Health and Needs
Now I am going to ask some questions about your healthcare situation
120.When was the last time you saw a doctor , a nurse or some other health care
professional:
This week, 1 week ago , 2 wks ago,
months ago, 5 months ago,
6 months ago,

1 year ago,

3 wks ago,

2 years ago,

1 month ago,

3 years ago,

N/A,

2 months ago,

3 months ago,

Other:

121.What kind of health-related problems, if any, do you have:

122.How often do you use protection against pregnancy or sexually transmitted diseases
(STDs):
All the time,

Never,

Often,

Rarely,

N/A

123.What kind of protection do you use:
Birth control, Check-ups with a doctor,

Condoms,

Wash/douche,

124.Have you ever had a sexually transmitted disease(STD):

N/A,

Other:

Yes,

125.What STDs, and how have you taken care of them:

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126.Do you have someone to talk to if you about your life situation or if you need help:
No,
Not sure,

Yes

127.Who do you feel most comfortable talking with about personal things:
Boyfriends, Cops, Counselor, Dealers/Gangsters, Families, Friends, Girlfriends, Johns, Pimps, Police,
Police,
Probation/parole officer, Residents, School, Service provider agent, Sex workers, Social service agency,
Store owners, Teacher,
N/A, Other:

128.What social service agencies, if any, are you aware of in your city area:

129.Have you ever gone to a social service agency for help with something:

No,

Yes

130.If no, why not:

131.If yes, which agencies:

132.If yes, what service(s) did you go for:

133.If yes, how often did you/do you go:

134.If yes, were they able to help you:

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135.Why or why not:

136.Do you use any of the following drugs :
Alcohol,

Cocaine/crack,

Heroin,

Marijuana,

Methamphetamines,

N/A, Other:

137.If yes, how old were you when you started using drugs or alcohol(probe for age of
serious drug use as well as first drug/alcohol usage):

138.How much do you spend on cigarettes, alcohol and drugs per day:

Experience With the Police
Next, I'd like to ask you a few questions about your experience with the police
139.How many run-ins with the police have you had:

140.What were these run-ins over:

141.How many were about sex-related activity:

142.Where have these run-ins taken place:

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143.How many occurred over the last year:

144.Do you give your real identifying information to the police:

Yes,

145.What happened last time when you interacted with the police(probe: has an officer
ever not arrested you in exchange for sex?):

146.Do you try to keep away from the police? If so, how?

147.How many times have you been arrested:

148.What were you arrested for:

149.When was the last time that you were arrested in this city area:

150.What were you arrested for:

151.Within the past year, how many times were arrested for prostitution related charges in
this city area?

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152.Have you ever been arrested outside of this city area:

Yes,

153.If yes, where:

Expectations
Now I am going to ask you some questions about your expectations for the
future.
154.Is there anything you like about this work:

No,

Not sure,

Yes

155.If yes, what do you like:

156.Is there anything you dislike about this work:

No,

Not sure,

Yes

157.If yes, what do you dislike:

158.Have you ever thought about leaving the life/this work:

No,

Not sure,

Yes

159.Have you talked to other people about leaving the life/this work: No,

Not sure,

Yes

160.if so, who:

161.Have you ever tried to leave the life/this work:

No,

Not sure,

Yes

162.If yes, how many times:

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163.If you wanted to leave this life tomorrow, would you know how:
Not sure,

No,

Yes

164.How would you do this:

165.Do you wish there were people who could help you make these changes:

166.Do you ever think of going back to school:

Yes,

167.Why or why not go back to school:

168.Would you like to find a better living arrangement:

Yes,

169.If yes, what kind of arrangement:

170.Has any social service agency ever approached you to offer services:

Yes,

171.Who:

Page 123

172.Comments: Note to interviewer: probe for whether contacts were CSEC specific or
for other issues.

173.Who would you go to when in trouble or doubt:
Boyfriends, Cops, Counselor, Dealers/Gangsters, Families, Friends, Girlfriends, Johns, Pimps, Police,
Police,
Probation/parole officer, Residents, School, Service provider agent, Sex workers, Social service agency,
Store owners, Teacher,
N/A, Other:

174.If there were an agency that existed just to meet your needs what would they offer?

175.Where do you see yourself in ten years?

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176.Is there anything else you would like to share with me:

Page 125

Appendix C. Social Service Providers
Interview Guide21
Introduction
Thank you for making the time to meet with me today. My name is __________. I’m a
researcher from the Center for Court Innovation (CCI) in New York City. Today’s interview is
part of a national project, funded by the Office of Juvenile Justice and Delinquency Prevention
(OJJDP), to learn more about the commercial sexual exploitation of children in the United States.
I’ll begin the interview by asking you some general questions about the organization you work
for, and then I’ll go into specifics about your organization’s experiences in trying to serve
children who are sexually exploited for commercial purposes. This interview is completely
confidential and voluntary. Your name will not appear in any published report or document.
The opinions and experiences you share will help researchers, practitioners and policymakers
understand the issues facing service providers as they try to address the needs of children who
are sexually exploited for commercial purposes. The interview will last about one hour.
Organizational Background (5 minutes)
First, I’d like to ask you some general questions about your organization.
1) What is the overall mission of your organization?
a. When was it founded?
b. How many people work for the organization?
2) What is your role within the organization?

At the stage of the study when we were conducting interviews with social service providers,
we used the term “commercial sexual exploitation of children” language, because this was the
original language of the OJJDP solicitation that we were funded under. Therefore, we adopted
“CSEC” terminology in our protocols. We later revised the language we used (i.e., throughout
this report) based on empirical findings.

Appendix C. Social Service Providers Interview Guide
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 126

[NOTE: The next questions are meant to gently get a sense of how well CSEC fits within the
overall organization. Is CSEC a main issue, an add-on or a far stretch? Do they work with
at-risk youth, on issues of prostitution, etc.?]
3) In general, what kind of services does your organization provide?
a. About how many clients does your organization serve each year?

CSEC Issue & Organizational Capacity (10 minutes)
Now, I’d like to talk more specifically about the commercial sexual exploitation of children
(CSEC).
4) How prevalent of an issue is the commercial sexual exploitation of children in your city?
[Note: specify the site]
a. Has it become more or less of an issue in recent years?
i. What has prompted these changes?
5) Where does the commercial sexual exploitation of children take place?
a. Public space (particular street corners, parks, alleys, etc)?
b. Massage parlors?
c. Motels?
d. Internet Sites?
e. Other?
[NOTE: Hand out a map and ask them to mark hotspots. Use map as a discussion
piece. Ask if CSEC occurs in similar places as prostitution.]
6) Is there a special unit or department within your organization that works with children
who are sexually exploited for commercial purposes?
a. If yes, about how many staff members are involved and what are their roles?
b. Do the staff members described above have any special training for working with
children who are sexually exploited?
c. How long has your organization been working on CSEC issues?
d. Does your organization have specific funding to work on CSEC issues? If yes,
what kinds of grants? (government, private, etc.)
7) How would you describe your CSEC clients in terms of characteristics?
a. Age
b. Gender
c. Race/Ethnicity
d. Recent Immigrants
e. Geographic areas of origin

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f. Types of CSEC [prostitution, internet pornography, other forms?]
8) Do CSEC clients differ demographically from your other clients? How so?

Outreach & Partnership Strategies (15 minutes)
Now, I’d like to ask some more specific questions about how your organization identifies
children who are sexually exploited for commercial purposes.
9) How does your organization first come in contact with children who are sexually
exploited for commercial purposes?
[NOTE: Try to get a sense of the process and level of networking involved.]
a. Do you have outreach workers who “pound the pavement” so to speak? If yes,
please describe how this works.
i. Do they work certain hours and locations?
ii. Do they work in teams?
iii. Are they on foot or in vans?
iv. How do they attempt to reach out to the children?
v. Do they speak at community forums, schools, police stations, etc?
vi. Do they post flyers?
vii. Other?
b. Do police officers, probation officers, prosecutors, judges, FBI agents or other CJ
officials refer children to your organization?
i. If yes, which CJ officials refer children?
ii. Is there a specialized unit?
iii. How does this process work?
iv. How would you describe these relationships?
c. Do other social service agencies refer children to your organization?
i. If yes, which agencies refer children?
ii. How does this work?
iii. How would you describe these relationships?
d. Do school officials refer children?
i. If yes, which school officials refer children?
ii. How does this work?
iii. How would you describe these relationships?
e. Of all the sexually exploited children your organization serves, about how are
most referred to your organization?
10) How do you view the local CJ agencies’ approach to CSEC?
a. Do the police/feds/courts see prostitutes as offenders or victims?
b. How would you classify the relationship between the local CJ agencies and the
children who are sexually exploited for commercial purposes?
11) Is your organization part of a special task force on the CSEC issue?

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a.
b.
c.
d.
e.
f.

If yes, when was this task force formed?
How often does the task force meet?
Who leads/convenes the meetings?
Who attends these meetings?
What are the goals of this task force?
What has the task force accomplished so far?

CSEC Service Delivery (15 minutes)
Now, I’d like to ask more about the kinds of services your organization provides to children
who are sexually exploited for commercial purposes.
12) Once a staff member makes an initial contact with a child who is thought to be sexually
exploited, what happens next?
a. Is there an intake assessment process/psycho-social evaluation?
[NOTE: If yes, get copy of the assessment.]
13) What kind of services does your organization provide for these children?
[NOTE: Take note of whether there are formal/structured programs, workshops and/or
classes, and the duration/number of sessions.]
Specify Service Description

Outreach
Counseling (self
esteem, sexual
assault, etc.)
Substance Abuse
Counseling

Housing

Food

Page 129

Medical Care
(general)
Employment
Assistance
Family
Reunification
School/Education
Assistance

Policy/Advocacy

Legal Assistance

Other

14) Does your organization refer children to other agencies for services? Please describe
these referral agencies and the services they provide.

Referral Organization/Agency

Service Type

15) Does your organization have any contact with pimps or johns?
a. If yes, what does that contact look like?
b. How does that contact form?
c. How do pimps or johns feel about your organization?

Page 130

Issues, Challenges & Promising Practices (15 minutes)
16) What do you think these children need to get out of the life?
a. Do you have any examples of children who have been successful?
If yes, how did they get out?
b. Are there any needs that are currently unmet/not being addressed?
17) What are some of the main issues that make it difficult to serve children who are sexually
exploited for commercial purposes?
[NOTE: Ask for specific examples]
18) What are some promising practices/strategies that seem to work well in serving these
children?
[NOTE: Ask for specific examples]
19) Does your organization have any data or case management records on the number of
children served?
a. Any data on what happens to these children?
b. What indicators do you track? (demographics, program participation, outcomes?
c. Would you be willing to share any of this data with us?
[NOTE: If yes, be sure to follow up on how to obtain data.]
Closing
Thank you for your time! As we wrap up the interview, there are just two things I’d like to
ask. One is that I would like to know if you can recommend other people in your city that I
should talk with regarding the CSEC issue.

Page 131

Names

Contact Information

Police Officers

FBI Agents

Judges

Prosecutors
Service
Providers

Others

Thanks again!

Page 132

Appendix D. Youth Interviews: Bulleted
List of Select Significant Differences
by Subgroup
Age


Recruitment of Customers: Younger participants ages 13-17 (78%) were significantly
more likely than ages 18-24 (61%) to get customers from the street (p<.05). Younger
participants ages 13-17 (49%) were also significantly more likely than ages 18-24 (36%)
to get customers from friends (p<.01).



Health Problems: Older participants ages 18-24 (79%) were significantly more likely
than ages 13-17 (46%) to have health problems (p<.01).



Social Service Agency: Controlling for time in life, older participants ages 18-24 (55%)
were significantly more likely than ages 13-17 (36%) to have gone to a social services
agency for help (p<.001).



Arrest History: Older participants ages 18-24 (69%) were significantly more likely than
ages 13-17 (51%) to have been arrested (p<.001). Older participants ages 18-24 (19%)
were significantly more likely than ages 13-17 (4%) to have been arrested outside city
(p<.001).



Dislike about the Work: Older participants ages 18-24 (88%) were significantly more
likely than ages 13-17 (76%) to say there was something they dislike about the work
(p<.001).



Leaving the Life: Older participants ages 18-24 (66%) were significantly more likely
than ages 13-17 (49%) to say they had tried to leave the life (p<.001). Older participants
ages 18-24 (67%) were significantly more likely than ages 13-17 (50%) to say they
would know how to leave the life (p<.001).



Housing Needs: Older participants ages 18-24 (50%) were significantly more likely than
ages 13-17 (36%) to say social services agencies should offer help with housing or
utilities (p<.01).

Appendix D. Youth Interviews: Bulleted List of Select Significant Differences
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 133

Race/Ethnicity


Parent Status: White participants (34%) were significantly more likely to be parents
than black/African American participants (28%) and multi-racial participants (23%)
(p<.01).



Age Left Home: White participants (15.8) reported leaving home significantly later than
Hispanic participants (14.3) and black/African American participants (14.8) (p<.01).



Age First Traded Sex: White participants (17.2) reported first trading sex at a
significantly older age than Multi-racial (15.4), Black/African American (15.5), and
Hispanic/Latino (15.8) participants (p<.001).



Other Source of Income: White participants (55%) are more significantly likely than
Black/African American participants (37%) to have another source of income (p<.01).



Social Service Agency: White participants (66%) were significantly more likely than
Black/African American participants (46%) to visit a social services agency (p<.01).



Drug Use: White participants (38%) were significantly more likely than all other
ethnicities (7%) to use heroin (p<.001). White participants (49%) were significantly more
likely than all other ethnicities (16%) to use drugs other than alcohol, marijuana,
cocaine/crack, or heroin (p<.001).



Arrest History: White participants (80%) were significantly more likely to have been
arrested than black/African American participants (61%) (p<.05).



Leaving the Life: White participants (83%) were significantly more likely to know how
to leave the life than Black/African American participants (57%) (p<.01).

Sexual Orientation


Education Level: Participants who identified as gay (62%) and those identifying their
sexual orientation as “other” (63%) were significantly more likely to report having a 12th
grade education or greater than other sexual orientations (45%) (p<.10) .



Age Left Home: Gay participants (24%) and those identifying their sexual orientation as
“other” (25%) were significantly more likely than bisexuals (10%) and heterosexuals
(12%) to have left home between the ages of 18-24 (p<.05).



Living at Home: Gay participants (8.8%) were significantly less likely than
heterosexuals (16.8%) to still live at home (p<.05).

Page 134



Use of Internet to Get Customers: Gay participants (63%) were significantly more
likely than heterosexuals (36%) to use the internet to get customers (p<.001).



Social Service Agency: Gay participants (64%) were significantly more likely than
heterosexuals (48%) to have visited a social services agency (p<.05).



Housing Needs: Gay participants (64%) were significantly more likely than
heterosexuals (42%) to say that the ideal social services agency would offer help with
housing/utilities.



Drug Use: Gay participants (92%) were significantly more likely than heterosexuals
(80%) to have used drugs and/or alcohol (p<.05).



Arrest History: Gay participants (75%) were significantly more likely to have been
arrested than heterosexuals (60%) (p<.05).



Leaving the Life: Gay participants (79%) were more likely than all other sexual
orientations (52%) to know how to leave the life (p<.05).

Parent Status


Hours Worked and Earnings: Parents (2.2) worked significantly more hours in the last
week than non-parents (1.9) (p<.05). Parents make significantly more per week than nonparents (p<.01).



Working with a Pimp: Controlling for age and gender, parents (22%) were significantly
more likely than non-parents (13%) to have a pimp (p<.01).



Food Stamps: Controlling for age, gender, sexual orientation, and ethnicity, parents
(19%) were significantly more likely than non-parents (8%) to seek food stamps from a
social services agency.



Leaving the Life: Controlling for age, gender, sexual orientation, and ethnicity, parents
(74%) were significantly more likely than non-parents (57%) to say that they had tried to
leave the life (p<.001).



Housing Needs: Controlling for age, gender, sexual orientation, and ethnicity, parents
(55%) were significantly more likely than non-parents (43%) to say that the ideal social
services agency would offer help with housing/utilities (p<.01).

Page 135

Appendix E. Youth Interviews: All Responses by Site
Table 1: Demographic Characteristics
Site
Number of Cases
Age
Mean age
13
14
15
16
17
18
19
20
21
22
23
24
Age Categories
13-17 years
18-24 years

TOTAL
947

US Born**

Atlantic
City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

19
0%
1%
2%
6%
12%
18%
20%
12%
11%
6%
7%
6%

20
0%
0%
0%
1%
11%
16%
18%
13%
7%
12%
7%
13%

20
0%
0%
1%
1%
5%
14%
18%
16%
16%
9%
15%
5%

19
0%
0%
1%
4%
3%
26%
9%
15%
30%
8%
4%
1%

19
1%
1%
2%
6%
6%
14%
15%
12%
17%
6%
10%
9%

18
1%
1%
4%
14%
25%
22%
29%
1%
2%
0%
1%
0%

19
0%
2%
2%
4%
7%
15%
16%
27%
10%
6%
3%
10%

21%
79%

12%
88%

7%
93%

8%
92%

16%
84%

46%
55%

14%
86%

97%

96%

98%

99%

100%

92%

99%

Appendix E. Youth Interviews: All Responses by Site
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 136

Site

TOTAL

Atlantic
City
Chicago

Dallas

Las
Vegas

Miami

Bay Area

Gender
Cis Male
Cis Female
Trans Female
Trans Male

36%
60%
4%
1%

31%
69%
0%
0%

47%
41%
11%
1%

28%
63%
8%
1%

36%
61%
2%
1%

37%
62%
1%
0%

24%
74%
2%
1%

Sexual Orientation
Heterosexual
Bisexual
Homosexual
Other

53%
36%
9%
2%

46%
52%
2%
0%

46%
33%
17%
4%

49%
21%
27%
3%

69%
27%
4%
1%

53%
42%
4%
0%

48%
36%
11%
5%

Ethnicity
Black/African American
White
Hispanic/Latino
Other
Multi-racial

70%
12%
7%
3%
8%

23%
54%
12%
5%
6%

80%
3%
7%
3%
7%

86%
3%
1%
0%
10%

57%
22%
11%
4%
6%

92%
0%
3%
0%
4%

47%
15%
11%
6%
21%

Education Level
Less than 6th Grade
6th-8th Grade
9th-11th Grade
12th Grade and above

0%
5%
48%
47%

0%
4%
56%
40%

0%
2%
37%
61%

0%
1%
38%
61%

1%
3%
44%
52%

0%
9%
58%
33%

0%
5%
48%
47%

Have Children

30%

46%

32%

39%

34%

19%

28%

Page 137

Site

TOTAL

Atlantic
City
Chicago

Dallas

Las
Vegas

Miami

Bay Area

How old when first left home?
Mean for those who had left home
Still lives at home

15
15%

15.8
9%

15.5
10%

14.5
2%

15.3
4%

14.1
34%

14.4
10%

Age at first sex experience
Mean
0-12
13-17
18-24

13
32%
64%
4%

13
35%
53%
7%

13
25%
64%
7%

12
37%
60%
3%

13
22%
73%
5%

12
35%
64%
1%

12
38%
59%
3%

First sex experience was nonconsensual

24%

33%

14%

37%

18%

25%

± Number non-missing data varied between 640 and 947.
+ p<.10, * p<.05, ** p<.01, ***p<.001.

Page 138

Table 2: Market Involvement
Site
Number of Cases

TOTAL
920

Atlantic
City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

What age first sold sex?
Mean

7%
70%
23%

4%
60%
36%

5%
66%
29%

7%
73%
20%

4%
68%
29%

13%
82%
5%

6%
68%
26%

Time in "the life"
Less than 1 year
1 year
3 years
4 years
5-9 years
10 or more years

11%
17%
35%
13%
22%
2%

11%
23%
28%
10%
25%
4%

9%
18%
32%
14%
24%
3%

13%
10%
36%
19%
22%
0%

15%
24%
34%
7%
18%
2%

6%
16%
40%
15%
23%
0%

16%
11%
35%
15%
19%
5%

Say there conflicts in the neighborhood where they work?

53%

46%

50%

60%

44%

60%

Say any conflicts have led to physical fights

35%

53%

33%

56%

27%

39%

Age Categories
0-12
13-17
18-24

Number of non-missing cases varied between 734 and 920
+p<.10, * p<.05, ** p<.01, ***p<.001.

Page 139

Table 3: Making and Spending Money
Site
Number of Cases

TOTAL
833

Atlantic City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

How many hours did you work last week?
0 hours
1-10 hours
11-20 hours
21-30 hours
31-40 hours
More than 40 hours

13%
39%
15%
12%
8%
13%

6%
29%
11%
17%
11%
26%

9%
46%
16%
16%
7%
5%

5%
28%
22%
15%
10%
19%

16%
45%
16%
5%
7%
12%

5%
41%
16%
16%
9%
14%

40%
35%
8%
6%
5%
7%

Amount charged to last customer
< $100
$101-200
$201-$300
> $300
Mean
Median

43%
32%
11%
13%
$190
$100

30%
36%
15%
19%
$254
$150

47%
27%
13%
14%
$244
$100

32%
45%
6%
17%
$181
$120

42%
25%
14%
20%
$213
$120

48%
35%
11%
7%
$142
$100

47%
35%
7%
11%
$143
$100

How much do you make in a week?
$0 / No longer working
< $100
$100 - $300
$301 - $600
$601 - $1000
$1001 - $1500
> $1500

1%
5%
26%
28%
21%
7%
12%

6%
1%
10%
25%
17%
15%
25%

6%
35%
27%
19%
6%
8%

0%
2%
20%
31%
23%
12%
12%

1%
7%
27%
22%
16%
11%
16%

1%
3%
32%
33%
22%
3%
6%

3%
5%
18%
28%
30%
3%
14%

Page 140

Site

TOTAL

Atlantic City

Chicago

Dallas

Las
Vegas

Miami

Bay Area

First thing you buy when paid?±±
Clothes or shoes
Food
Rent or other bills
Drugs/Alcohol
Cigarettes
Items for children
Other

39%
32%
26%
19%
7%
11%
35%

18%
31%
29%
41%
18%
13%
13%

47%
39%
36%
15%
12%
10%
46%

45%
35%
18%
8%
1%
19%
39%

38%
36%
34%
25%
8%
10%
34%

53%
31%
25%
12%
1%
13%
41%

18%
20%
7%
19%
7%
4%
24%

Report having other sources of income

42%

50%

49%

36%

44%

19%

52%

Report owing anyone money

20%

28%

20%

29%

23%

10%

± Number non-missing data varied between 663 and 833.
±±Multiple responses allowed for each question.

Page 141

Table 4: Customers
Site
Number of Cases

TOTAL
900

Atlantic
City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

Where do you get customers?±±
Street
Internet
Friends
Referral
Pimp
Regulars
Other (Parties, Casinos, Strip Clubs, etc.)

63%
42%
39%
26%
9%
3%
18%

62%
13%
28%
22%
8%
8%
29%

57%
41%
33%
20%
4%
5%
18%

34%
51%
35%
31%
13%
3%
1%

49%
36%
35%
18%
4%
0%
19%

79%
48%
59%
42%
10%
0%
18%

79%
52%
0%
0%
19%
-

Average number of customers seen each day/night
0
1-2
3-5
6-10
>10
Mean
Median

1%
31%
43%
19%
7%
5
4

0%
22%
36%
26%
16%
6
5

2%
43%
37%
12%
7%
4
3

0%
32%
40%
22%
6%
5
3

2%
33%
46%
14%
5%
4
3

0%
21%
48%
25%
6%
5
4

1%
34%
41%
20%
4%
4
3

How often customers from pimp?
Never
Rarely
Often
All the time

76%
11%
7%
6%

77%
10%
2%
11%

75%
16%
6%
4%

82%
5%
7%
7%

78%
7%
7%
8%

75%
9%
11%
5%

74%
16%
6%
4%

Of those who have pimp: report internet was used to get customers

41%

50%

37%

36%

45%

41%

40%

Of self-generated customers: Report internet was used

46%

35%

49%

42%

36%

50%

49%

Number of non-missing cases varied between 271 and 900.
±±
Multiple responses allowed for each question.
Appendix E. Youth Interviews: All Responses by Site
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.

Page 142

Table 5: Pimps

Site
Number of Cases
Report working with a pimp
Of those with a pimp, reporting the pimp has rules
Report working with a market facilitator who is not a pimp

TOTAL
949

Atlantic
City
98

Chicago
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

15%

11%

17%

13%

14%

29%

42%

28%

43%

16%

43%

54%

72%

19%

36%

19%

10%

24%

11%

21%

Number of non-missing cases varied between 325 and 949
+ p<.10, * p<.05, ** p<.01, ***p<.001.

Page 143

Table 6: Experience with the Police
Site
Number of Cases

TOTAL
825

Atlantic
City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

Ever arrested

65%

88%

70%

87%

55%

59%

62%

Ever arrested for prostitution

16%

31%

10%

23%

10%

17%

Arrested for prostitution in the last year

11%

23%

19%

12%

11%

Ever arrested outside city of interview

16%

66%

16%

21%

Number of non-missing cases varied between 718 and 825
+ p<.10, * p<.05, ** p<.01, ***p<.001

Page 144

Table 7: Health and Needs
Site
Number of Cases
When did you last see a doctor?
< 3 Months Ago
3-6 Months Ago
7-12 Months Ago
Over a year ago

TOTAL
878

Atlantic
Las
City
Chicago Dallas Vegas Miami
98
202
78
171
264

Bay Area
136

65%
18%
10%
7%

69%
5%
17%
10%

72%
14%
7%
7%

83%
15%
3%
0%

60%
17%
15%
8%

54%
27%
11%
8%

What kind of health problems, if any, do you have?
None
Sex-related
Non-sex-related physical
Mental Health-Related
Multiple

65%
27%
4%
2%
2%

54%
5%
33%
6%
2%

59%
3%
34%
2%
2%

25%
8%
7%
0%
0%

69%
3%
21%
4%
3%

78%
6%
16%
0%
1%

How often do you use protection against pregnancy and STIs?
All the time
Often
Sometimes
Rarely/Never/NA

82%
12%
3%
3%

87%
7%
1%
5%

86%
8%
6%
0%

91%
5%
3%
1%

89%
7%
3%
2%

77%
18%
5%
0%

73%
19%
5%
4%

Ever had an STI

31%

22%

37%

40%

25%

24%

46%

Have someone to talk to about life situation or when help is needed

72%

74%

82%

75%

62%

77%

Ever gone to a social services agency for help

51%

64%

50%

47%

53%

33%

75%

69%
20%
6%
5%

Page 145

Site

TOTAL

Atlantic
Las
City
Chicago Dallas Vegas Miami

Bay Area

Service provided by social services agency±±
Of those who had been to a service agency:
Housing or Rent
Counseling/Mental Health
Food Stamps
STI Treatment/Prevention/Pregnancy Testing
Food

20%
13%
12%
11%
10%

26%
9%
17%
7%
20%

18%
14%
6%
8%
10%

16%
3%
6%
21%
6%

11%
2%
20%
4%
4%

14%
23%
12%
19%
4%

41%
26%
7%
17%
19%

Use any drugs or alcohol

84%

77%

85%

93%

86%

82%

Use any of the following drugs±±
Marijuana
Alcohol
Cocaine/Crack
Heroin
Other

66%
58%
13%
7%
20%

49%
22%
43%
35%
25%

66%
61%
4%
0%
12%

74%
64%
6%
0%
4%

71%
63%
14%
9%
34%

68%
63%
11%
1%
19%

Number non-missing data varied between 560 and 878.

±±

Multiple responses allowed for each question.
+p<.10, * p<.05, ** p<.01, ***p<.001

Page 146

Table 8: Expectations
Site
Number of Cases±
EXPECTATIONS
Is there anything you like about this work?
Yes
No
Not sure

TOTAL
825

Atlantic
City
Chicago
98
202

Dallas
78

Las
Vegas
171

Miami
264

Bay Area
136

72%
27%
1%

57%
43%
0%

61%
37%
2%

65%
33%
3%

77%
22%
1%

85%
15%
1%

70%
29%
2%

Is there anything you dislike about this work?
Yes
No
Not sure

83%
15%
1%

92%
7%
1%

86%
12%
2%

88%
9%
3%

89%
12%
0%

71%
28%
1%

91%
8%
1%

Ever tried to leave the life?

62%

70%

81%

68%

59%

42%

74%

If wanted to leave the life tomorrow, would know how

63%

67%

72%

63%

81%

46%

65%

Ever approached by social service agency to offer services

19%

13%

24%

20%

10%

13%

35%

If there were an agency that existed just to meet your needs what
would they offer?
Employment/Education
Housing/Utilities
Food/Money
Counseling/Advice
Addiction Services/Healthcare/Sex Ed

49%
47%
36%
16%
11%

35%
52%
34%
20%
21%

64%
54%
26%
20%
7%

55%
44%
34%
10%
8%

56%
51%
42%
16%
18%

38%
39%
38%
15%
5%

Number of non-missing cases varied between 718 and 825
+p<.10, * p<.05, ** p<.01, ***p<.001.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.