The author(s) shown below used Federal funds provided by the U.S. 

Department of Justice and prepared the following final report:

Document Title: The Nature and Extent of Gang Involvement in 

Sex Trafficking in San Diego County

Author(s): Ami Carpenter, Ph.D., Jamie Gates, Ph.D.

Document No.: 249857

Date Received: April 2016

Award Number: 2012-R2-CX-0028

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.
Project Title: The Nature and Extent of Gang Involvement in Sex Trafficking

in San Diego County

Award Number: NIJ- 2012-R2-CX-0028

Author(s): Ami Carpenter, PhD and Jamie Gates, PhD

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.
2

The Nature and Extent of Gang Involvement in Sex Trafficking 

in San Diego County

Final Report

Submitted to

United States Department of Justice

Office of Justice Programs

National Institute of Justice

Grant No.: NIJ- 2012-R2-CX-0028

Prepared by

Ami Carpenter, PhD

Principal Investigator

Joan B. Kroc School of Peace Studies

University of San Diego

5998 Alcala Park, Suite 113

San Diego, CA 92110

Tel: (619) 260-7830

Email: acarpenter@sandiego.edu 

Jamie Gates, PhD

Co-Investigator 

Department of Sociology and Social 

Work

Pt. Loma Nazarene University

3900 Lomaland Drive

San Diego, CA 92106

Tel: (619) 849-2659

Email: jamiegates@pointloma.edu

Jan 2016

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.
3

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.
4

TABLE OF CONTENTS

FOREWORD

ACKNOWLEDGEMENTS

EXECUTIVE SUMMARY

I. INTRODUCTION 

I.A BACKGROUND

I.B KEY TERMS AND DEFINITIONS

I.C STATE OF KNOWLEDGE ABOUT GANG INVOLVEMENT IN SEX TRAFFICKING

I.D MINING EXISTING AND REACHING INTO NEW DATA SOURCES

I.E ACTION-BASED RESEARCH AND COMMUNITY COLLABORATION

II. METHODS 

II.A SITE SELECTION: SAN DIEGO COUNTY AND BORDER REGION

II.B SAN DIEGO COUNTY HUMAN TRAFFICKING AND CSEC ADVISORY COUNCIL

II.C STUDY DESIGN: TRIANGULATION OF DATA FROM MULTIPLE SOURCES

II.D DATA COLLECTION

II.D.1. Survey Data on Victims from Freedom from Exploitation (FFE) 

II.D.2. Victims Intake Data from Social Service Providers (TVIT) 

II.D.3. Arrest and Booking Data from Law Enforcement Agencies 

II.D.4. Focus Groups in San Diego County High Schools 

II.D.5. Individuals Involved with or Knowledgeable about Sex Trafficking 

II.E Study Design Limitations 

II.E.1. Trafficking Victims Identification Tool (TVIT) 

II.E.2. Law Enforcement Data 

II.E.3. School Focus Group 

II.E.4. In-Depth Interviews with Incarcerated Individuals 

III. FINDINGS AND ANALYSIS 

III.A SCALE OF THE ILLICIT SEX ECONOMY IN SAN DIEGO

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.
5

III.B TRAFFICKERS

III.B.1. Scope of Sex Trafficking Facilitation 

III.B.2. Nature of Gang Involvement in Sex Trafficking 

III.C VICTIMS

III.C.1. Profile of San Diego Victims 

III.C.2. Recruitment in San Diego High Schools 

IV. DISCUSSION 

IV.A SUMMARY OF FINDINGS

IV.B IMPLICATIONS FOR POLICY AND LAW ENFORCEMENT PRACTICES

IV.C FUTURE RESEARCH ON SEX TRAFFICKING AND GANGS

V. REFERENCES 

VI. TABLES AND FIGURES 

VII. APPENDICES 

VII.A INTERVIEW GUIDELINE FOR FACILITATORS

VII.B GLOSSARY OF TERMS

VII.C GANG STRUCTURE ANALYSIS

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.
6

FOREWORD

This project was conducted under Grant No. NIJ- 2012-R2-CX-0028 awarded by the National 

Institute of Justice, Office of Justice Programs, United States Department of Justice. Points of 

view in this document are solely those of the author and do not necessarily represent the official 

position or policies of the United States Government. 

SUGGESTED CITATION

Carpenter, A. C. and Gates, J. (2016). The Nature and Extent of Gang Involvement in Sex 

Trafficking in San Diego County. San Diego, CA: University of San Diego and Point Loma 

Nazarene University.

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.
7

ACKNOWLEDGEMENTS

This research would not have been possible without the support, trust and collaboration 

of a wide range of San Diego leaders and community members. We are in particular grateful for 

the collaboration of those that partner under the banner of the San Diego County Regional 

Advisory Council on County Human and Child Sex Trafficking. In particular, the authors thank 

its partners and subcontractors for their support and hard work: the San Diego Sheriff’s 

Department, Freedom from Exploitation, San Diego County Schools and select school districts, 

SecDev Cyber, Bilateral Safety Corridor Coalition (BSCC), San Diego Youth Services (SDYS) 

STARS program, La Maestra Community Health Centers, GenerateHope, North County Lifeline, 

San Diego Adolescent Pregnancy and Parenting Program (SANDAPP), Mary’s Guest House, 

and SDS Hope House. 

The authors are tremendously grateful for the hard work and patience of research 

assistants Lars Almquist, Sophie Callahan, Natalie Hsieh, and Tasi Rodriguez. Our research 

proposal and first year of work benefited tremendously from the contributions of Dr. Dana Nurge 

at San Diego State University. We thank Josette Ford and Laura Curtis at the San Diego Sheriff’s 

Department for their excellent analytical advice and continuous support to the research team. To 

the leaders of San Diego’s Human Trafficking Survivors Support Network and all of the 

survivors of human trafficking who shared parts of their story with us, we are eternally grateful. 

Finally, we give special recognition to Chief Deputy District Attorney Summer Stephan, for her 

guidance and wisdom in navigating the complex law enforcement system in San Diego County, 

and her unwavering support for anti-trafficking efforts in San Diego County.

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.
8

THIS PAGE LEFT INTENTIONALLY BLANK 

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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.
9

EXECUTIVE SUMMARY

INTRODUCTION

In 2011, San Diego County created the multi-agency San Diego County Regional Human 

Trafficking and Commercial Sexual Exploitation of Children Advisory Council with the 

objective to reduce human trafficking and commercial sexual exploitation of children in San 

Diego County and the Mexico border region through prevention, prosecution, protection and 

partnerships. As co-chairs of the Research and Data Sub-Committee of this advisory council, 

Drs. Carpenter and Gates were asked to pursue a research agenda that would help develop robust 

measures of the scope of human trafficking in San Diego County. Of particular interest to the 

County Advisory Council was empirical evidence of the suspected relationship between gangs 

and human trafficking. 

BACKGROUND AND STUDY OBJECTIVES 

The overall purpose of this project was to investigate the nature and assess of the scope of 

gang involvement in sex trafficking in San Diego County. Human trafficking is a global 

phenomenon with a variety of local manifestations, including labor and sex trafficking. San 

Diego is ranked by the FBI as one of the nation’s 13 highest areas of commercial sexual 

exploitation of children. Despite widespread attention on sex trafficking, there has been little 

empirical research on the nature and process of sex trafficking activities, and even less on the 

connection between sex trafficking and gangs. Prior to this study, much of what was known 

about sex trafficking in San Diego County was anecdotal and descriptive. The study’s basic 

premise was that empirical investigation would prove useful for both policy and practice.

This 3-year study reports on three major sets of findings: (1) the scope and nature of gang 

involvement in sex trafficking and commercial sexual activity, including detailed analysis of sex 

trafficking facilitation (2) the scope of nature of victimization in San Diego County, and (3) 

estimates of the regional commercial sex economy. It was designed to improve on seven 

shortcomings in human or sex trafficking research thus far:

 

 

1. Few credible estimates of the scale of sex trafficking in a particular region 

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.
10

2. The common conflation of commercial sexual exploitation and prostitution with 

sex trafficking

3. Lack of primary data on sex trafficking1 

4. Inability to identify networks of sex traffickers 

5. Understudied extent of gang involvement in sex trafficking 

6. Over-reliance on qualitative methods 

7. Small sample sizes

METHODS AND DATA COLLECTION

We used mixed-methods to gather data (qualitative and quantitative) from five major 

sources: (1) surveys conducted across ten years with 702 participants in a prostitution first 

offender diversion program, (2) standardized intake forms with 140 sex trafficking survivors 

conducted across our two year study window by eight nonprofits that provide direct services to 

human trafficking victims, (3) combined Police arrest records and Sheriff booking datasets, (4) 

focus groups with staff at 20 high schools in San Diego County, and (5) in depth interviews with 

gang affiliated individuals involved in or knowledgeable about sex trafficking.

Data gathered from these five sources was collated into four major datasets: Survivor 

Services Dataset, Law Enforcement Reporting Dataset, Schools Dataset, and Facilitator2

Interview Dataset. Triangulation and analysis of these datasets generated quantitative and 

qualitative findings that shed light on the scale and complex challenges associated with 

Commercial Sexual Exploitation of People (CSEP)3

, Commercial Sexual Exploitation of 

Children (CSEC)4, and Commercial Sexual Activity (CSA) defined broadly as sex acts for 

compensation (monetary, other). 

 

1 Studies often rely instead on secondary sources - newspaper reports and media investigations, or 

interviews with intermediaries: social service providers, counselors, law enforcement, victim advocates, pro bono 

attorneys, and others working with trafficking victims

2

 Facilitator refers to the person/s using force, fraud or coercion for commercial sexual exploitation; 

collaborators who benefit financially; and all those involved in CSEC.

3

 This term refers to all persons, regardless of age, who have been sexually exploited through the exchange 

of sex or sexual acts for drugs, food, shelter, protection, other basics of life, and/or money. CSEC is a subcategory of 

CSEP.

4

 This term refers to the sexual abuse of a minor “entirely, or at least primarily, for financial or other 

economic reasons. The economic exchanges involved may be either monetary or non-monetary (i.e., for food, 

shelter, drugs).” Richard J. Estes & Neil Alan Weiner, Univ. of Pa., The Commercial Sexual Exploitation of 

Children In the U.S., Canada and Mexico 10 (rev. Feb. 20, 2002), avail- able at 

http://www.sp2.upenn.edu/restes/CSEC_Files/Complete_CSEC_020220.pdf.

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.
11

FINDINGS

Three main categories of findings emerged from this study: (1) estimates of the regional 

commercial sex economy, (2) the scope and nature of gang involvement in sex trafficking, and 

(3) the scope and nature of sex trafficking victimization.

(1) ESTIMATES OF THE REGIONAL COMMERCIAL SEX ECONOMY

We estimate the size of the illicit sex economy in San Diego County in 2013 at $810 

million dollars. We reached this number by duplicating and modifying the methods used by the 

Urban Institute to estimate the size of the underground sex economy in San Diego California in 

their 2014 study, with two changes. First, we included two industries in our estimate of the cash 

economy in San Diego that Urban Institute had not – recreation and gambling – industries that 

intuition might naturally associate with cash spending. In brief, it may be that Dank et al. (2014) 

considerably underestimated the size of the cash stock in San Diego, which likely biases 

downward their estimates of the illicit sex economy, as well.

Second, with data from 56 sex trafficking facilitators, including 46 incarcerated 

interviewees and 10 facilitators we interviewed in the community, we were able to generate more 

robust estimates of what sex trafficking facilitators earn. Whereas Urban Institute estimated 

trafficker earn $528,000 per year in San Diego, this study found that facilitators make on average 

$670,625 per year (based on the assumption that facilitators only take 75% of the revenue 

generated by each commercial act). 5

(2) SCOPE AND NATURE OF GANG INVOLVEMENT IN SEX TRAFFICKING

Scope

Evidence from 154 criminally involved persons, 140 victims of sex trafficking and 141 

staff members of 20 high schools spread across San Diego County led us to discover 110 gangs 

in San Diego County from a wide variety of neighborhoods and racial/ethnic backgrounds that 

 

5

 50% is the most oft-cited percentage of sex worker earnings charged by sex facilitators. Some report as low 

as 15% or as high as 100%.

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.
12

have members that are engaged in profiting from sex trafficking in San Diego. The level of 

centralization and organization of sex trafficking activity among these gangs varies significantly 

from cliques and sets that loosely affiliate with the gang for protection while they act 

independently to centrally organized units with a centralized taxation system, even transnational 

criminal networks.

Our interviews produced strong evidence that gangs in San Diego are engaged in the 

commercial sexual exploitation of people and children (CSEP and CSEC). Of our sample of 

persons in protective custody in San Diego County jails, 52.5% (76/139) identified or were 

identified with a street gang. We identified 33% (46/139) of those interviewed as sex trafficking 

facilitators, and 80% (37/46) of those that identified as sex trafficking facilitators affiliated with 

a gang. In all, we interviewed self-identified facilitators (46 in jail and 10 in the community), 

and only nine (16%) denied any gang affiliation. 

Organization

There exist many types of relationships between individual facilitators and the gangs with 

which they affiliate. Relationships range from individuals selling sex on the side (with no 

involvement from – or profit to – their gang), small cliques of members (in some cases 

collaborating with other groups or individuals outside of gang), to significant proportion of 

members involved & the group or at least group leaders profit. In some cases, individuals not 

involved in gangs reported that they have working relationships with gangs or gang members.

These relationships reflect different levels of organizational complexity. We drew a 

distinction between directed sex trafficking, defined as individual activities dictated by, and 

directly profiting, a gang and undirected sex trafficking, defined as individual activities not 

dictated by, and directly profiting, a gang. We found that facilitation in San Diego County was 

almost evenly split between directed and undirected: Out of 72 gang members (34 of whom 

were facilitators, and 38 of whom did not identify as facilitators but who had knowledge of how 

‘pimping’ worked in their gang) 25 reported that ‘pimping’ was purely entrepreneurial 

(undirected), 29 reported that it was an operation taxed and/or organized by their gang, and 14 

facilitators reported arrangements and understandings that represented both directed and 

undirected facilitation.6

 Directed trafficking is positively and significantly associated with gangs 

 

6 An additional 4 interviews were coded ‘inconclusive’ on this question.

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.
13

that have clear rules of conduct, and a promotion structure. Gang members’ use of violence is 

also positively and significantly associated with gang organizational complexity, specifically 

territoriality, duration, role differentiation, promotion, and tax structure.

Race

We encountered roughly equal numbers of White (34%) and Black (32%) facilitators of 

sex trafficking during interviews in the jails, with Hispanics coming in third (24%). In fact, the 

ratio of white to minority facilitators may be higher than is reported here given that our data does 

not account for the over-representation of Black and Hispanic inmates in California jails. Nor 

does the relatively even split between Black, Hispanic and White facilitators represent a 

complete picture. For example, in recent years, Somali gangs and Iraqi Chaldean groups have 

been indicted on sex trafficking charges, and Asian American and Native American gangs were 

under-represented in our dataset. Our data cannot extrapolate to percentages of all population 

groups given this under-representation of significant gang populations.

Coerciveness

The three most commonly used types of coercion reported by trafficking facilitators in 

our sample were: 

● Economic Coercion (74%)

Defined by a high percentage of earnings (50% or above) taken by facilitator. 

● Psychological Coercion (57%)

Defined as social and emotional isolation, induced emotional exhaustion, and 

degradation, including humiliation, denial of the victim's power, and name-calling.7

● Chemical Coercion (42%)

Refers to bringing about altered states of consciousness either by providing drugs, or 

forcing drugs. 

The use of violent coercion was reported by only 12% of facilitators (Physical and 

Sexual). Facilitators often talked about how those who have to use violence were not as skilled 

as those who employed psychological techniques. We suspect the level of violent-vicious 

 

7 Our definition of psychological coercion is adapted from BIDERMAN'S CHART OF COERCION. 

Amnesty International, Report on Torture (New York: Farra, Strauss, and Giroux), 1973. The additional four grades 

of force were defined by Ami C. Carpenter.

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.
14

facilitation is underreported by facilitators themselves as between 14%-30% of victim/survivors 

report experiencing violence at the hands of their “pimp” or trafficker.8

Facilitator Profile

Interviews with 61 facilitators (46 incarcerated, 15 community) generated four broad 

profiles of how sex-trafficking facilitators identify themselves and their role. The most common 

self-identification of facilitators was as Enforcer-Contractor (67%). Enforcer-Contractors reject 

the ‘pimp’ label. They claim to work with adults only, and often described being recruited by 

women already involved in CSA. They argue that they function mainly as drivers and provide 

security against rape and violence from the buyers, or from others trying to control their 

commercial sex activity. Though the percentages vary, Enforcer-Contractors report that revenue 

is shared between the facilitator and the one involved in the commercial sex act, making this one 

of the main distinction from Traditional facilitators.

Traditional facilitators (28% of our sample) are most likely to use the term ‘pimp’ to 

describe themselves. They describe the pimp identity in terms of status and recognition. They 

keep all, or most of money made in each sexual encounter.

Vicious-Violent9(4% of our sample) facilitators use extreme tactics of physical and 

psychological control to force high financial quotas. They are willing, and perhaps prefer, to 

 

8

 14.5% of the 702 first time prostitution offenders from FFE reported experiencing violence (86 

individuals reported being forced to have sex “because of a violent pimp” and 16 individuals “to avoid a beating”). 

A higher 30% (43) of the 140 sex trafficking survivors confirmed by the SSP8 reported experiencing violence at the 

hands of their pimp or trafficker. Three possible explanations exist for the variation between datasets. First, we are 

missing data from 95 additional individuals from the SSP8, because we were retrospectively coding intake forms 

This information simply was not present either in their file, or in the recollection of intake staff. Perhaps many more 

individuals experienced violence – perhaps not. Secondly, the demographic of the two different populations is very 

different. FFE is a program for all individuals arrested for the first time, for prostitution. In other words, it is a wide 

net (all first time offenders) in a very narrow sea (visible ‘prostitutes’) cast by law enforcement. CSEP account for 

50% of that dataset, but the other 50% consists of adult men and women involved in CSA who either work without 

pimps, are in are in more consensual relationships with them (described in more detail below), are sex hobbyists, 

etc. SSP8 programs for individuals referred specifically because they have been trafficked. It is a narrow net 

(trafficked people) in a wide sea (forced labor ) cast by law enforcement + schools, child welfare organizations, 

family members, friends, etc. CSEP accounts for 84% of that dataset, and their demographics are different. Third, 

the FFE dataset extends twelve years (from 2003-2015), whereas the SSP7 extends only two (from 2013-2015). We 

believe trends in sex trafficking have changed a great deal in the last decade.

9 The common street language for this category in San Diego is “Gorilla Pimp.” We have chosen 

“Vicious-Violent Facilitator” as a descriptive term to avoid the racial stereotyping embedded in this term in our 

context, a stereotyping we believe contributes to ignoring the varying degrees of violent behavior in all population 

groups. 

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.
15

recruit minors because of the malleability and vulnerability of young people. They control every 

aspect of commercial sexual exploitation.

The fourth type of sex-trafficking facilitator identified in San Diego is Organized 

Trafficking Groups (OTGs) in San Diego. OTGs are structured as clandestine, closed networks, 

run by a small core group of individuals. Examples include a multinational “black book” ring 

that trades in adults and minors; a child prostitution ring controlling both domestic and 

international individuals; a residential brothel trafficking children from the Philippines; and a 

MS-13 clique operating as a closed group that traffics individuals minors and adults from 

southern Mexico. While none of our interviewees admitted to being involved in OTGs, 

numerous gave specific detail of their knowledge of such activities.

Online Presence

Consistently interviewees mentioned the way that the selling of sex has moved from the 

streets predominantly online to sites like backpage.com, mobile brothels whose locations are 

advertised via Snapchat, social media and text based collaboration, as common examples. We 

found qualitative difference between the use of social media by African American versus Latino 

gangs. “While there is considerable evidence in the public domain of San Diego-based gangs - 

especially African American and so-called hybrid groups - having used specific social media 

tools such as Twitter to recruit and pimp out women and girls, it is not evident in the profiles of 

specific Latino cartel, gang or affiliate groups on either side of the border...It is possible, then, 

that gangs are simply not actively discussing their involvement or organizing operational 

activities associated with sex trafficking on Twitter” (Way and Muggah, 2015).

Transnational Connections

Canadian cyber-research firm SecDev was subcontracted to conduct social media 

research on gang activity, in order to document the nature of cross-border activity between San 

Diego gangs and Mexican armed groups. The study documented a significant empirical 

difference between the use of social media by African American versus Latino gangs. They 

documented “considerable evidence in the public domain of San Diego-based gangs - especially 

African American and so-called hybrid groups - having used specific social media tools such as 

Twitter to recruit and pimp out women and girls”. SecDev reported that social media based 

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.
16

activity around sex trafficking it is not evident in the profiles of specific Latino cartel, gang or 

affiliate groups on in San Diego. Despite being widely advertised online, there was virtually no 

evidence of Latino gang involvement in prostitution and sex work on Twitter. 

Location

Commercial sexual activity has moved off the streets and into hotels, casinos and 

residential brothels. We mined law enforcement data for location of prostitution, pimping and 

pandering arrests to identify locations where commercial sexual activity is most common. In 

2013 for example, the majority of arrests took place in just 13 locations, 10 of which were hotels. 

Facilitators also reported that hotels/motels are the most common site of CSA, in addition to 

casinos, and private homes.10 This pattern of activity is associated with concerted efforts by San 

Diego Police Department that targeted the most visible forms of street prostitution, e.g. El Cajon 

Blvd in 2011, and the desire by facilitators to avoid law enforcement by "staying off the street".

(3) SCOPE AND NATURE OF VICTIMIZATION

Scope

Based on arrests for sex trafficking crimes and our findings on the average number of 

victims controlled by facilitators we interviewed, our estimate of the total number of CSEP in 

San Diego County ranges from 3417-8108 per year. Based on estimates from parallel research on 

drug and gun trafficking (Goodman & Marizco, 2010; McDougal et al., 2014), we estimate that 

law enforcement only arrests 15-20% of the persons committing trafficking offenses. 

From analysis of our data from first time arrestees for prostitution, 50% of adults arrested 

for prostitution actually meet the federal definition for classification as victims of human 

trafficking, but are unidentified or misidentified within the criminal justice system. In addition, 

our analysis of law enforcement officer incidence reports related to domestic violence lead us to 

120 cases per annum that we would advise law enforcement to investigate more deeply on 

suspicion of sex trafficking.

 

10 We specifically asked facilitators about where prostitution was taking place, to make sure we controlled 

for the possibility that hotels were not simply the most common target for law enforcement sting operations (thereby 

showing up more frequently in arrest records) as opposed to actually being the most common site of CSA.

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.
17

Country of Origin

Sex-trafficking victims in the social service system are primarily born in the United 

States (79.3%). The next most significant country of birth is Mexico (11.4%) with less than 10% 

of victims born in one of the following countries: Cameroon, China, Colombia, Germany, 

Honduras, Kazakhstan, Korea, Philippines, Puerto Rico, Russia, and Taiwan.

Age and Residence

Combining data from our sample of 302 adult sex trafficking victims identified among 

first time arrestees for prostitution with data from 321 minors in the same program, we estimate 

that the average age of entry into sex trafficking in San Diego County is 16.1 years of age. 

Although no community in San Diego is untouched by CSE, the majority of trafficked 

individuals live in 10 zip codes. Each of these zip codes identifies a particular neighborhood or 

area of the city that is home to one or more street gangs. To give just three examples, 92113 

(Logan Heights) has seven street gangs; 92114 (Southeast San Diego) has six gangs; and 92102 

(Golden Hill; Market Street) is home to four gangs with multiple cliques.

Homelessness/Foster Care

We found a strong correlation between victimization, homelessness and foster care. Of 

our sample of sex trafficking victims among those arrested for prostitution, 55% reported that 

they were or had been homeless and 28% reported they had been in foster care. Those who had 

gone through foster care were 2.63 times (P>|z|=0.000) more likely to be homeless than those 

who had not gone through foster care.

Recruitment at High Schools

Of the sex trafficking facilitator we interviewed in county jails, 30% reported they have 

participated in or witnessed sex trafficking connected to middle schools and high schools. All 20 

high schools that participated in this study confirmed that recruitment was happening with their 

students; 90% (18 schools) reported documented cases of sex trafficking victimization. 

In total, 141 staff members from 20 high schools across the county identified 81 reported victims 

along with an additional 54 suspected victims in the past 5 years. Staff across these 20 schools 

also identified 17 recruiters targeting their campuses. Staff also named 31 distinct gangs linked 

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.
18

in some fashion to sex trafficking, with an additional 7 unnamed gangs involved. In total, 69 

named gangs were given by school staff as active in/near these schools with an additional 15 

unnamed gangs listed as active). 

DISCUSSION

These findings have a variety of implications for San Diego County stakeholders to 

consider. In this section we discuss the issues raised, the implications these issues have on 

policy for our region and beyond and the implications this project has for future research. While 

there are a myriad of findings to be explored from this data in greater detail, here are our 

interpretations of some of the most significant findings:

First, the scale of the underground sex economy is considerably larger than that for which 

San Diego County has currently taken account or for which it is prepared. At $810m a year it 

rivals the income from macro-economic forces such as the Otay Mesa Port of Entry, the Natural 

Resources and Mining Sector, and is about the equivalent of what the San Diego Padres were 

sold for in 2012.

Second, the scope of sex trafficking in San Diego County is wider than expected. 

Virtually no community in San Diego remains untouched by sex trafficking. Victims have been 

identified either living or ‘working’ in every city in San Diego County, and in areas of each that 

are both wealthy and impoverished. One hundred percent of the 20 schools where we did focus 

groups, spread across North County, Central San Diego, South Bay and East County, had 

evidence of sex trafficking happening connected to their students. While we found evidence of 

victimization happening all in a wide range of neighborhoods, ten zip codes are home to a 

disproportionate number of victims and these zip codes correlate with underserved populations 

that deserve special attention.

Third, 110 gangs in San Diego County from a wide variety of neighborhoods and 

racial/ethnic backgrounds have members that are engaged in profiting from sex trafficking in San 

Diego. The level of centralization and organization of sex trafficking activity in the gang varies 

significantly, from cliques and sets that loosely affiliate with the gang for protection while they 

act independently, to centrally organized units with a centralized taxation system, even 

transnational criminal networks. As we have no baseline, we cannot judge quantitatively 

whether this is an increase or decrease from the past, but both the sex trafficking facilitators and 

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.
19

the law enforcement officials we interviewed agree that this is a growing income for San Diego 

area gangs. 

Fourth, as the likely first point of contact for victims of sex trafficking, for a variety of 

reasons law enforcement lacks sufficient information to correctly distinguish victims of sex 

trafficking from other related crimes (e.g. prostitution, domestic violence, sexual assault). Our 

finding that 50% of those arrested for prostitution related charges were at one point in their lives 

in fact sex trafficking victims suggests that the system (law enforcement, social services, schools, 

etc.) is not yet fine tuned enough to identify sex trafficking victimization at a sufficient scale. 

Further support to this concern is added by our analysis of law enforcement officer incidence 

reports related to domestic violence that lead us to approximately 120 cases per annum that we 

would advise law enforcement to investigate more deeply on suspicion of sex trafficking.

Fifth, further evidence for the need for greater examination of the connections between 

law enforcement, schools and social services comes from our findings that the median age at the 

time of a first arrest for prostitution is 19 years old while the average age of entry into sex 

trafficking is 16.1 years of age. As our “age of entry” estimate is conservative, this means that 

community leaders are unaware of the average victim being trafficked for about three years 

before they reach the attention of law enforcement. Further investigation will be needed to 

understand the full range of reasons why this gap exists. 

Sixth, the stereotype that sex trafficking is principally a practice of black gangs is 

inaccurate for San Diego County and may channel apprehension efforts by law enforcement in 

too narrow a direction. This disproportionate attention is in part driven by the highly visible 

social media presence of African American gangs on social media, making them “low hanging 

fruit” for law enforcement. They are not, however, the only subpopulations involved. Hispanic 

street gangs are believed not to participate in CSEP, but we found that many Hispanic gangs do 

participate in CSEP - some in a highly organized fashion, and some in purely entrepreneurial 

ways. A related problem is that, although a wide variety of gangs are involved in sex trafficking, 

many are loosely networked making them difficult to identify and track. 

Seventh, the world of sex trafficking as it relates to gangs is extremely complex and 

changing, with the structure and function of gangs shifting and morphing and facilitators playing 

a variety of roles. The majority of facilitators in our sample reported relying less on physical 

coercion than on exploitation of socioeconomic vulnerability, prior abuse in the home, drug 

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.
20

addiction, and mental health issues. This does not mean that highly coercive networks and 

organizations are not a major threat in our region, but the majority of sex trafficking activity 

identified in our interviews was dependent on skills to psychologically manipulate and coerce 

another person into sex for profit.

Eighth, qualitative responses from older facilitators and from our victims data suggests 

that teenagers (including minors) are being recruited into sex trafficking facilitation and as 

victims at rates previously unseen by older facilitators. A common refrain from facilitators is 

that the age of the up and coming facilitators is getting younger and younger. Combined with 

our victims data, where the average age of entry into sex trafficking is 16.1 years of age, a 

central reality that seems to be emerging is that our children and young adults are trafficking our 

children and young adults.

Policy Implications

Given the findings of this project, the participating researchers make the following 

recommendations to the San Diego County Regional Advisory Council on County Human and 

Child Sex Trafficking. The following recommendations can be sorted into three categories: 

capacity building, service delivery, and new programming. 

Capacity Building: Specific actions can be taken to engage in capacity-building efforts and 

to strengthen institutions on the ground, including bolstering the training of officials and 

frontline practitioners to enhance their engagement with communities.

1. Conduct assessments of local drivers of CSEP: Risk assessments and perception 

studies help people better understand the local drivers of vulnerability specific to their 

communities, and are key to providing baseline data to track the impact of counter human 

trafficking programming, and then drawing on those lessons to inform future 

programming.

2. Expand and regularize CSEP training for frontline officials and practitioners: Human 

trafficking is just coming into the formal training systems of frontline officials and 

practitioners. Practical trainings should be conducted for all frontline officials and 

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.
21

practitioners - on both sides of the border - who engage with groups of people who are 

vulnerable to recruitment into CSEP by gangs, those who are vulnerable to recruitment 

into facilitating CSEP, and those in both categories who have already been recruited. 

While front line law enforcement agents and officers are just being brought up to speed, 

and the social workers of the San Diego County Child Welfare Services are just being 

given new CSEC protocols, San Diego County should increase resources for the training 

of school personnel in identifiers and protocols, as well as awareness training for students 

from middle and high schools. San Diego would also do well to expand the trainings for 

healthcare professionals in the indicators and protocols. Given its prominence and social 

impact in San Diego, special concern has been raised in this study for increased 

awareness training for the military in all its facets.

3. Support Robust Community Policing: This study represented the first two steps 

(SCANNING AND ANALYSIS) of the SARA model of problem-oriented policing 

(Goldstein, 1979; Goldstein, 1990). The next two components - Response and Evaluation 

- require robust community policing - a philosophy that supports police-community 

partnerships and joint problem-solving - to encourage two-way information sharing and 

joint public safety initiatives. Community policing offers an opportunity to build trust and 

partnerships in communities that can help police protect against the criminal sexual 

exploitation of its members.

Service Delivery: The following recommendations involve specific actions to improve 

service delivery to victims of commercial sexual exploitation, and to deter would-be 

perpetrators. 

4. Increase support for victims and survivors: Supporting victims and survivors of CSEP 

is an imperative principle of justice, and San Diego is encouraged to expand 

rehabilitation of and support for victims of sex trafficking. Three issues are critical. 

4a. Eliminate existing ordinances that criminalize “child prostitution” and replace 

with laws that protect them as victims 

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.
22

4b. Address the shortage of facilities for victim-survivors. The County has just 29 

beds for rescued sex trafficking victims. None of them serve men, and none of 

them are human trafficking specific beds for minors. 

4c. Regularize collaboration between and among victim advocates and law 

enforcement as a measure to recognize and protect victims. 50% of prostitution 

arrests may in fact reflect cases of trafficking victims, and their safety, privacy, and 

physical and psychological well-being should be ensured. 

5. Amplify Survivor Voices: Amplifying the voices of victims and their stories can also 

contribute to exposing the brutality and hypocrisy of pimps, facilitators and their 

narratives. Survivors and family members can be powerful changemakers. 

New Programming: The following recommendations regard specific enhancements within 

security and criminal justice sectors, and introduce disengagement and reintegration 

programs. 

6. Prison-based Rehabilitation Interventions: San Diego County should develop prisonbased rehabilitation interventions for incarcerated facilitators, and programs to assist 

individuals who are at risk of being recruited into facilitation. 

7. Intentional Interface with Gang Intervention Programming already in place: San Diego 

is home to the Commission on Gang Prevention and Intervention, a network similar in 

diversity of membership to the HT Advisory Council. Its purpose is to prevent gangrelated violence, to disengage at risk youth, and to build relationships between vulnerable 

communities and San Diego governmental and law enforcement officials. The 

Commission has several time-tested programs that are natural entry points for engaging 

facilitators and those at risk of becoming involved. We strongly recommend and support 

working with former “pimps” and facilitators to foster disengagement and reintegration 

programs. 

8. Expand apprehension and prosecution efforts to buyers: If growing attention in San 

Diego is being paid to the sellers (facilitators) and the persons as products being sold in 

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.
23

San Diego’s sex trafficking market (victims), little policy and infrastructural attention is 

being given to curbing the demand (buyers). The disincentives for buyers are relatively 

inconsequential and the facilitators argue that they are just filling a market demand. We 

recommend both stronger policy addressing demand and public awareness campaigns to 

make the broader public, especially potential buyers, more aware of the true costs of the 

underground sex economy in San Diego.

Future Research

Collaborative Research: The results of this research make a strong case for building 

national databases from the ground up, funding researchers with local and regional expertise to 

develop partnerships across the sectors needed for access to data and the populations to be 

researched. The partnerships we nurtured through our involvement in the San Diego County 

Regional Advisory Council on Human Trafficking and CSEC helped us (1) address research 

questions that are most pressing to those working to raise awareness, curb sex trafficking 

activity, intervene with gangs, and rescue/rehabilitate victims, (2) gain access to databases and 

populations that in the case of sex trafficking research would otherwise have remained hidden 

and (3) have the most likelihood of impacting public policy and infrastructure for positive 

change. National policy will be strengthened by the comparative application of lessons learned 

from the most robust local and regional measures.

Scale: The surprising scale of the underground sex economy in San Diego demands 

continued refinement of regional empirical measures of the illicit sex economy, triangulating 

findings from other sources, tracking change over time and greater attention to disaggregation of 

sex trafficking activity from the rest of the illicit sex economy. 

Gangs: We consider this research a baseline empirical analysis of the relationship 

between gangs and sex trafficking in San Diego County. While 110 gangs were named in this 

research, data on each of these gangs was received from a small number of persons in each gang. 

Future researchers can build a more ethnographically rich profile from a wider representation of 

each of these gangs in order to better understand the changing dynamics and significance of gang 

life in San Diego County. 

Law Enforcement: The collaborative nature of San Diego’s movement to address human 

trafficking, combined with the legitimacy conferred by funding from the National Institute for 

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.
24

Justice, gave researchers on this project broad and trusted access to non-public data from a wide 

variety of law enforcement agencies in San Diego County, the Sheriff and the San Diego Police 

Department in particular. Through this level of access we were able to compare measurements 

and findings across jurisdictions, something that during the course of our research our regional 

law enforcement agencies were working to improve. The dialogue between our research team, 

law enforcement analysts and community based-researchers helped to develop greater insight 

and more refined empirical measures for each of our respective roles.

Social Services: As many who research sex trafficking from the perspective of social 

services know, the standardization of measures that identify sex trafficking victims is a work in 

progress. This research extended the regionally vetted research done by the Vera Institute in 

New York by field testing a portion of the standardized Trafficking Victim Identification Tool 

they developed here in San Diego. The eight social service agencies found parts of the tool 

helpful, and other parts they wanted to modify. The research raised debate about and helped to 

refine where in the intake process such tools are best administered. While still in process as of 

the writing of this report, the network of social service agencies that collaborate under the 

Victims Services umbrella of the San Diego County Regional Advisory Council on Human 

Trafficking and CSEC are using this research to outline a regionally appropriate intake 

assessment tool.

Schools: The most exploratory part of our research was the focus groups we conducted in 

20 high schools across San Diego County, spread across Central San Diego, the South Bay, East 

County and North County. Having identified what school officials think is happening at their 

schools, a strong follow up research project would be to collect data from the students 

themselves. One path toward collecting data from students we recommend is to add questions 

about sex trafficking to standardized student response surveys that already are in use. 

Social Media Analytics: Social media analytics methods are capable of effectively 

detecting, identifying, tracking, and monitoring the ongoing communications, interactions, 

activities and operations of criminal gangs in the U.S. and Mexico. When pursued cautiously and 

mindful of biases, it can usefully supplement ongoing investigations into the domestic and 

transnational dynamics of cartel and gang activities. 

Collaboration among researchers: An important practice and outcome of this project has 

been the regular interaction of a network of regionally based researchers studying various aspects 

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.
25

of human tracking. As co-chairs of the Research and Data Subcommittee of the San Diego 

County Regional Advisory Council on Human Trafficking and CSEC, the study’s investigators 

hosted quarterly gatherings of other university-based researchers, graduate students, law 

enforcement analysts, social service research experts and community-based researchers to 

collaborate on various dimensions of research. The San Diego County Board of Supervisors saw 

such value in the collaborative gathering of researchers we were modeling that they decided to 

fund what we called HT-RADAR (Human Trafficking Research and Data Advisory Roundtable), 

i.e. the ongoing coordination of county-wide human trafficking research. We advocate for the 

continued support and spread of this research-based contextual policy making.

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.
26

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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.
27

The Nature and Extent of Gang Involvement in Sex Trafficking in San Diego County

Award Number: NIJ- 2012-R2-CX-0028

I. INTRODUCTION 

Between 2011 and 2015 three major federal cases brought evidence of street gang 

members organizing sex trafficking activities in San Diego County. The first case to raise 

concern was an indictment of 38 individual associated with the “Oceanside Crip enterprise” 

operating a sex trafficking ring out of a hotel in Oceanside in April of 2011 (FBI, 2011).11 In 

January of 2014 a second major case involved an indictment of 24 individuals associated with 

“BMS,” an alliance of street gangs that were sex trafficking girls in 46 cities across 23 states 

(USDOJ, 2015).12 And in December of 2014, 22 alleged members of the “Tycoons” were 

indicted for operating a nationwide prostitution enterprise primarily from East County San 

Diego; this case involved many underage girls that were recruited from area middle and high 

schools (FBI, 2014).13 While the need to better understand what is perceived as an increasing 

connection between street gangs and sex trafficking activities raised by local law enforcement 

and regional social service providers served as the foundational motivation for this project, the 

connection is also becoming of significant interest for research and investigation across the 

United States (FBI, 2010; Haas 2010).

The overall purpose of this project was to investigate the nature and assess the scope of 

gang involvement in sex trafficking in San Diego County. Sex trafficking is a subset of human 

trafficking, a crime akin to modern-day slavery and a global security and justice challenge. 

Almost every country in the world is affected by human trafficking, according to the United 

Nations Office on Drugs and Crime (UNODC), the guardian agency of the United Nations 

Convention on Transnational Organized Crime and its Protocol to Prevent, Suppress and Punish 

 

11 Oceanside Crip enterprise (“Oceanside Crips”) is reportedly composed of various Crip gang “sets,” 

including the “Insane Crip Gang,” “Deep Valley Crips” and “Crook, Mob, Gangsters.

12

 “The organization was known as “BMS,” which is a combination of “Black MOB” and “Skanless” 

gangs, and these members are also allegedly aligned with other streets gangs, including Neighborhood Crips, 

Lincoln Park, and West Coast Crips, among others. 

13 Federal Bureau of Investigation, San Diego Division, Alleged Gang Members and Associates Indicted 

in Cross-Country Sex Trafficking Conspiracy

https://www.fbi.gov/sandiego/press-releases/2014/alleged-gang-members-and-associates-indicted-in-crosscountry-sex-trafficking-conspiracy

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.
28

Trafficking in Persons, especially Women and Children”. The so-called flesh trade is also 

operationally linked to other trans-border issues including the illicit drug trade, organized crime, 

and terrorism prevention (Berkovitch and Jackson, 2012; Abadinsky, 2010; Sanderson, 2004; 

Väyrynen, 2003; Jamieson, 2001).

Human trafficking is a global phenomenon with a strong local presence. Much of what 

was known about sex trafficking in San Diego was anecdotal and descriptive and/or contained 

within proprietary law enforcement circles. Our basic premise was that empirical investigation 

would help cross-reference, verify and improve on what is known from law enforcement, social 

service and public education sources, identify gaps in the sources of data currently used to 

identify sex trafficking activities and victims, and prove useful for both policy and practice 

across a wide range of sectors. This project focused narrowly on one of the most under-studied 

aspects of human trafficking in the United States: the relationship of street gangs as facilitators 

of sex trafficking (National Gang Threat Assessment, 2011). 

I.A. Background

In November 2009, the San Diego County Board of Supervisors held a presentation on 

gang involvement in prostitution and the use of underage girls as prostitutes, and asked County 

Administrators to come up with a regional approach to address human trafficking and child 

prostitution. In June 2011, the San Diego County Board of Supervisors unanimously voted to 

form the San Diego Regional Human Trafficking and Commercial Sexual Exploitation of 

Children (RHT- CSEC) Advisory Council led by San Diego County District Attorney and 

Sheriff’s Office. The Council consists of six subcommittees – Victim Services, Law 

Enforcement, Schools and Education, Policy, and Data/Research - and a Coordinating 

Committee for subcommittee chairs to share information, coordinate work with each other, and 

ultimately provide consensus policy advice to the County Board of Supervisors for better policy 

and legislation to fight and prevent human trafficking.

The research proposal submitted to NIJ in 2012 was the result of 10 months of discussion 

between RHT-CSEC committee members. The proposal was authored as the first step towards 

meeting the Advisory Council’s top priority: defining the scope of human trafficking in the San 

Diego/Tijuana region by consolidating and integrating the information and data systems that 

each member brings to the table. 

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.
29

Weitzer (2014) identified four best practices for anti human trafficking research, and this 

study meets three out of the four. First, he advises researchers to shift focus from international 

and national (macro) level studies to town/city (micro) level studies. “Microlevel studies offer 

the best promise for yielding reliable data on trafficking - information that can be used by the 

authorities to properly target efforts to combat coercive and deceptive practices (169). Our lens 

was focused on the County level, albeit with a strategic eye towards the US-Mexico border. We 

would not have been able to manage the complexity of the research design had we chosen a 

larger level of analysis. 

Second, researchers are advised to use multiple research methods. We combined 

quantitative and qualitative research methods to collect and integrate existing social service and 

law enforcement databases, and to diversify the sources of data to include high schools and 

traffickers themselves. This multi-method research design was specifically developed in order to 

triangulate data from multiple sources, each of which offers valuable information in our effort to 

understand the hidden industry of trafficking in San Diego County. It built on Carpenter’s (2012) 

pilot study of street-gang activities in the San Diego-Tijuana border region during which she 

conducted in-depth interviews with gang workers, law enforcement, victim service providers, 

and former gang members in order to piece together a social network analysis of inter-group 

collaboration, and GIS maps of concentrated activity. 

Third, researchers are advised to advance to large-n studies: building on - but going 

beyond - the very useful research findings generated by previous small-n case studies. Our 

research design involved gathering and analyzing data from hundreds of current and former gang 

members, schools, law enforcement agencies, and victim service providers. In all, data was 

collected from 1205 individuals, making this one of the largest, most comprehensive human 

trafficking case studies in the United States to date: 156 gang affiliated persons, 702 first-time 

prostitution offenders, 189 survivors from eight victim services programs, and 140 County 

School administrators and staff. 

Because of its narrow focus, however, the study falls short of Weitzer’s fourth best 

practice: shifting focus from sex-trafficking to the larger issue of labor trafficking. This study 

singled out sex trafficking, limiting attention given to other forms of trafficking in our region. 

We recognize and accept this limitation as necessary given that one of our primary goals was 

specifically to explore the role of gangs and we felt that including all labor trafficking would 

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.
30

have constituted too broad a research agenda. As preliminary evidence pointing to gang 

involvement in labor trafficking is all but non-existent in San Diego County, we prioritized 

researching the link between gangs and sex trafficking.

Overall, this study represents the result of collaborative research to impact policy and 

practice that we hope will serve as a national model for future research on human trafficking 

more broadly. The key concepts behind our approach were collaboration and integration. 

Collaborative information sharing by law enforcement agencies, victim services organizations, 

and schools made possible the analytical outputs of this study. The collaborative research design 

permitted this research project to integrate previously disparate datasets, and extended 

integration to include data gathered from high schools, and from traffickers and active members 

of gang. 

I.B. Key Terms and Definitions

Under U.S. federal law, victims of human trafficking include children involved in the sex 

trade, adults age 18 or over who are coerced or deceived into commercial sex acts, and anyone 

forced into different forms of "labor or services," such as domestic workers held in a home, or 

farm-workers forced to labor against their will. In 2000, the U.S. Congress passed the Victims of 

Trafficking and Violence Protection Act (VTVPA) (22 U.S.C 7101), which was amended in 

2003, 2005, and 2008. The federal law views children who are induced to commit commercial 

sex acts as victims of violent crime and not as criminals. 

In 2005, the State of California passed Assembly Bill 22, which added Penal Code 236.1, 

making the trafficking of any person for the purposes of labor or commercial sexual exploitation 

a felony crime. Human Trafficking is defined by California Penal Code, in §236, as: “Any person 

who deprives or violates the personal liberty of another with the intent to effect or maintain a 

felony violation of Section 266, 266h, 266i, 267, 311.4, or 518, or to obtain forced labor or 

services, is guilty of human trafficking.”(C.P.C.§236) The law further delineates that in order to 

charge human trafficking there must be: “Unlawful deprivation or violation of the personal

liberty of another includes substantial and sustained restriction of another's liberty accomplished 

through fraud, deceit, coercion, violence, duress, menace, or threat of unlawful injury to the 

victim or to another person, under circumstances where the person receiving or apprehending the 

threat reasonably believes that it is likely that the person making the threat would carry it 

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.
31

out.”(C.P.C.§236) The penal code mandates that a person found guilty of human trafficking can 

be sentenced to state prison for three to five years. If the victim is under the age of 18, the 

sentence to state prison is four to eight years. 

Sex trafficking and pimping are terms that are often used interchangeably due to the 

nature of the crime. In order to successfully convict a charge of human trafficking, the prosecutor 

has to prove force, fraud or coercion. This differs from pimping, which is legally determined by 

the monetary gain an individual receives from a prostitute. However, the reality is that girls from 

the United States are being recruited into prostitution by manipulation, coercion, and abuse and 

their recruiter is typically a “pimp” who profits (Grace, 2010; Raphael & Shapiro, 2002). 

Therefore, for the most part, human sex trafficking and pimping co-occur (Morgan, 2012).

Prostitution is defined by California law as an exchange of any lewd act for money or 

other considerations (Legislative Council of California, n.d.e). The California Penal Code in 

§647b states: “A person agrees to engage in an act of prostitution when, with specific intent to so 

engage, he or she manifests an acceptance of an offer or solicitation to so engage, regardless of 

whether the offer or solicitation was made by a person who also possessed the specific intent to 

engage in prostitution. No agreement to engage in an act of prostitution shall constitute a 

violation of this subdivision unless some act, in addition to the agreement, is done within this 

state in furtherance of the commission of an act of prostitution by the person agreeing to engage 

in that act” (C.P.C. §647b). A prostitution offense in California is a misdemeanor; if found 

guilty, a first time offender is sentenced to a maximum of 30 days in county jail. 

This study used the term victim to refer to individuals who experienced sex trafficking or 

forced prostitution. Referring to an individual who was pimped or trafficked as a victim is 

becoming more common among practitioners and researchers due to an enhanced understanding 

of the circumstances that lead to this status and an effort to de-stigmatize the individual as they 

are handled through law enforcement or social services practices. The victim may knowingly 

break the law, but may more typically do so through the coercion and control of a 

pimp/trafficker. At the same time, victim advocates are using the term survivor more and more 

often to convey personal agency and the power of renewal that is so important to recovery from 

exploitation. Some survivors remain in the depths of victimization, not yet in any semblance of 

recovery, and may thus be termed victims. Victim/survivor is one alternative when writing about 

individuals who have experienced commercial sexual exploitation, but we chose victim due to 

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.
32

this being the baseline experience of all victim/survivors, including those who are yet to break 

free and those who have long since become thriving survivors.

Females are the most common victims of prostitution and trafficking. Whereas the 

exploitation of young men may be more uncommon internationally (Burke et al., 2007; Guillen, 

2006), domestic girls and women are the ones primarily recruited for sex trafficking in San 

Diego County. The population of prostituted victims in the U.S. typically ranges between 13 and 

25 years old. A nationwide survey revealed 89 percent of prostituted victims were over 14 years 

old; 90 percent were female; all juveniles were United States citizens; 59 percent of the victims 

were white and 36 percent were black; 60 percent had history of running away; and 36 percent 

had criminal records at the time of their present arrest (Mitchell et al., 2010) In San Diego, 

victims of sexual exploitation were 84 percent more likely to report being abused in the past by 

either a family member or a family friend than the other interviewees (Burke et al, 2007).

In §266h, the California Penal Code describes a pimp as a person who deprives personal 

liberty from another by collecting their earnings from sexual acts for money. The legal definition 

for pimping is: “Any person who, knowing another person is a prostitute, lives or derives support 

or maintenance in whole or in part from the earnings or proceeds of the person's prostitution, or 

from money loaned or advanced to or charged against that person by any keeper or manager or 

inmate of a house or other place where prostitution is practiced or allowed, or who solicits or 

receives compensation for soliciting for the person, is guilty of pimping, a felony, and shall be 

punishable by imprisonment in the state prison for three, four, or six years” (C.P.C. §266h).

A related criminal offense found in research and criminal codes is pandering. While the 

definition of pimping refers to a person’s act, pandering refers to the act itself. In California, 

pandering is defined in §266i(2) as an individual who, “promises, threatens violence, or by any 

device or scheme, causes, induces, persuades, or encourages another person to become a 

prostitute”(C.P.C. §266i(2)). In other words, pandering can be charged against a pimp who 

recruits and teaches a prostitute the ‘rules of the game’ of prostitution. In 2009, due to variation 

in pimping rules, the California Appellate court decided in People v. Wagner to expand 

pandering to include a prostitute’s new pimp, even if she had been taught the ‘rules of the game’ 

by a different pimp (Court of Appeal, Fourth District, 2009). Essentially this means that even if a 

young woman has been the victim of a previous pimp, the law allows for the new pimp to be 

charged with pandering since his rules may differ from another pimp’s rule. 

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.
33

This study will refer to facilitators of sex trafficking (hereafter ‘facilitators’) instead of 

pimps. The primary reason, discussed at length further on, is that ‘pimp’ is a socio-culturally 

imbued term with which only some people involved in CSEP identify. The majority of 

individuals interviewed rejected the term (meaning they did not refer to themselves as ‘pimps’) 

while admitting to the variety of behaviors described by the pimping penal code. Therefore, 

pimping and pandering are mostly referred to as penal codes throughout this report, not as social 

identities. Facilitator refers to the person/s using force, fraud or coercion for commercial sexual 

exploitation of people (CSEP); collaborators who benefit financially; and all those involved in 

CSEC.

Commercial Sexual Exploitation of People (CSEP) is a new term introduced by this 

study. CSEP refers to all persons, regardless of age, who have been sexually exploited through 

the exchange of sex or sexual acts for drugs, food, shelter, protection, other basics of life, and/or 

money. CSEC (Commercial Sexual Exploitation of Children) is defined as a subcategory of 

CSEP. CSEC refers to the sexual abuse of a minor “entirely, or at least primarily, for financial or 

other economic reasons. The economic exchanges involved may be either monetary or nonmonetary [i.e., for food, shelter, drugs]” (Estes and Weiner, 2001). 

I.C. Gang Involved Sex Trafficking in San Diego

San Diego County is located in the Southwest corner of the state of California and shares 

its southern border with Mexico. While gangs are present throughout the County, the city of San 

Diego, in particular, has a “significant gang problem”(Baker and Hall 2011). Although the actual 

number of gang-involved individuals is potentially much higher, there are approximately 4,100 

registered gang members,14 less than five percent of them juveniles, in the City of San Diego 

(Baker and Hall 2011).

The state of California enacted Penal Code 186.20, the California Street Terrorism 

Enforcement and Prevention Act (S.T.E.P. Act), to combat the “violent street gangs whose 

members threaten, terrorize, and commit a multitude of crimes against the peaceful citizens of 

 

14 An individual must meet certain criteria to be documented. Community advocates have raised concerns 

about the gang documentation process through San Diego’s Commission on Gang Prevention and Intervention. 

Aware of higher punishments with the S.T.E.P. Act, some gang members avoid being documented. The 

requirements can be found on the San Diego Police Department’s Frequently Asked Questions Regarding Gang 

Documentation (http://www.sandiego.gov/police/pdf/gangfaq.pdf)

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.
34

their neighborhoods,” and to aid in the prosecution of gang members. Gangs are defined in this 

report according to Section 186.22 of the S.T.E.P Act as follows:

“Criminal street gang” means any ongoing organization, association, or group of three or 

more persons, whether formal or informal, having as one its primary activities the 

commission of one or more of the criminal act enumerated in paragraphs (1) to (25) 

inclusive of subdivision (e), having a common name or common identifying sign or 

symbol, and whose members individually or collectively engage in or have engaged in a 

pattern of criminal gang activity. (C.P.C.186.22)

The California Penal Code further explains that “criminal gang activity” is to be defined as the, 

“commission of, attempted commission of, conspiracy to commit, or solicitation of, sustained 

juvenile petition for, or conviction” of two or more of the following offenses: assault with a 

deadly weapon, robbery, homicide, sale or manufacture of a controlled substance, shooting at an 

unoccupied dwelling or vehicle, shooting a firearm from a vehicle, arson, or any of the 27 other 

felonies listed.

In 2011, the number of street gangs in San Diego County was estimated at 170 

(Cavanaugh and Tintocalis, 2011). Hispanic gangs are deeply embedded in US-Mexico border 

communities through generations of family members. African American gangs, including 

Bloods and Crips sets, have an established presence.15 In addition, being a refugee resettlement 

city, San Diego is home to a wide variety of ethnic gangs as well: Somali Crips sets, Iraqi 

Chaldean criminal networks, Pacific Islander gangs, Chinese Triads, and a myriad of smaller 

groups organized around Tongan, Vietnamese, Laotian, Thai and other ethnic identities, also 

operate. 

While gangs are present in almost every neighborhood in San Diego, the majority of 

them are concentrated in the more socially disadvantaged neighborhoods of the city and within 

the Mid-City, Southeastern, Central and Southern police divisions (Carpenter and Cooper, 2015). 

Gang territories are among the more violent areas of the city San Diego.16 While potentially gang 

 

15 The City of San Diego has the “highest number of street gangs in the county [and] most claim Mid-City 

and Southeastern community”. See Cavanaugh, 2011. 

16 Gangs cluster in disadvantaged and disorganized neighborhoods often characterized by poverty, 

inequality and family disruption. See Carpenter (2012). 

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.
35

related17 violent incidents occur throughout the city, the majority of violent incidents take place 

within the mapped gang-territories (Carpenter, 2012). From January 2009-November 2011, 

there were 226 incidents of unlawful homicide or manslaughter18. Over 60 percent of them took 

place in an active gang area. Conversely, only 35 percent of the narcotic related arrests occurred 

within the mapped gang territories.

In addition to incidents of homicide and manslaughter, other violent crimes are 

concentrated in these areas as well. Within the three year period for which San Diego Police 

Department provided incident data, almost half of all violent incidents19 occurred within the 

mapped gang territories, including over 40 percent of the crimes violating penal code 245 

(assault with a deadly weapon or by means of force likely to produce great bodily injury), both 

incidents of attempted murder, and 75 percent of the kidnappings. More than 50 percent of the 

deadly weapon20 arrests and over 50 percent of carjackings occurred in these specific areas as 

well (ibid). 

There has been minimal research done on the relationship between gangs and sex 

trafficking or prostitution in San Diego County. The link between street gangs and sex 

trafficking has gained increasing national and statewide attention in the last five years from law 

enforcement and social service agencies, and is just coming on the radar of policymakers.21

 In 

2011 Laura Lederer combed through federal court cases and identified more than 200 federal 

cases of street gangs, motorcycle gangs and prison gangs in which commercial sex acts, 

prostitution or human trafficking are mentioned (Lederer, 2011). California Attorney General 

Kamala Harris noted in her 2012 State of Human Trafficking in California Report,

 

17 Qualifying offenses under PC 186.22, the S.T.E.P. Act.

18 Violation of California Penal Code 187.

19 The file included approximately 4,600 violent incidents including: Aggravated mayhem, Mayhem, 

Assault with a deadly weapon or by means of force likely to produce great bodily injury, Attempted Murder, 

Kidnapping, Rape, Shooting at an inhabited dwelling or occupied motor vehicle, Torture and Unlawful homicide or 

manslaughter.

20 Deadly weapon charges include PC 12021 - Prohibited possession of a firearm; PC 12025 -Carrying a 

concealed firearm; PC 12101 - possession of a pistol, revolver, or other firearm capable of being concealed upon the 

person; HS 11550 - under Influence-Narcotic-W/Firearm.

21 See, e.g., Laura J. Lederer, Sold for Sex: The Link Between Street Gangs and Trafficking in Persons, 4 

PROTECTION PROJECT Journal of Human Rights & Civil Society 1, 1 (2011); Kamala D. Harris, CA Department 

of Justice, The State of Human Trafficking in California, 63-64 (2012), available at 

http://oag.ca.gov/sites/all/files/pdfs/ht/human-trafficking-2012.pdf

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.
36

Local and transnational gangs are increasingly trafficking in human beings because it is a 

low-risk and high, renewable profit crime. It is critical for federal, state, and local law 

enforcement and labor regulators to collaborate across jurisdictions to disrupt and 

dismantle these increasingly sophisticated, organized criminal networks (Harris 2012).

Urban law enforcement agencies were starting to make the association between gangs and 

trafficking by late 2000s, and empirical research was not far behind. Dorais and Corriveau’s

2008 study in Montreal was the first to thoroughly examine the issue. In the United States, 

Raphael and Myers-Powell (2010) study of former pimps and madams in Chicago made 

anecdotal references to gang involvement, both as ‘hired’ security for prostitutes, and vehicles 

for organized prostitution operations. However their study was not set up to look specifically at 

the prevalence of gang involvement in pimping. An earlier NIJ funded project (Curtis et al, 

2008) studied youth prostitution in New York and reported that pimps were not key to “initiating 

youth into the market or controlling them once they were in the market” (5).

Our study emerged from observations by law enforcement and victim service providers 

that gangs were increasingly becoming involved in sex trafficking. Gangs in San Diego have 

evolved and grown over the past 20 years. A 1998 study concluded that gangs in San Diego were 

relatively unorganized: unlikely to specialize in a particular type of crime (such as pimping), 

unable to reap significant profits from their illicit activities, and unlikely to have alliances or 

business relationships with other gangs, particularly rivals (Decker, Bynum and Weisel, 1998). 

The authors at that time described San Diego as an “emerging gang city”. By 2004, the National 

Drug Intelligence Center reported that San Diego was a hub for gang distribution of marijuana 

(National Drug Threat Assessment, 2004), and ten years later the San Diego Association of 

Governments (SANDAG) reported that San Diego County was home to over 155 gangs, and that 

1 in 4 adults and over 40% of juveniles in detention facilities countywide reported some form of 

gang affiliation (2014). 

In 2007 the ACTION Network (Against Child Trafficking and The Prostitution of Teens 

In Our Neighborhoods) through the San Diego Association of Governments (SANDAG) 

conducted the first region-wide research on the sexual exploitation of children that began to 

examine the commercial sexual exploitation of children at some scale. The study was conducted 

at a time when it was more common to talk about “prostituted teens” and examined the broader 

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.
37

topic of child and youth sexual exploitation. But contained in the study is a convenience sample 

of 200 “homeless, runaway and other vulnerable youth 25 years of age and younger” (SANDAG 

2007). In this study, one in three surveyed youth reported being sexually exploited and another 

one in five had been approached in the past and asked to engage in acts of prostitution. “Many 

of those who provided input noted that gangs are now more involved in the prostitution of teens, 

due in part to the perception it is more profitable and less risky than some other illegal 

enterprises” (SANDAG 2007). This research opened insights into how widespread the 

commercial sex exploitation of children and youth and pointed toward the need for more 

systematic data collection methods.

In a 2014 study of inmates in the San Diego prison system, 27% of gang members 

admitted to “pimping or prostitution” with their gang (SANDAG 2014). Comparing the 

“pimping” activity of gang-affiliated vs. non-gang-affiliated inmates, gang-affiliated inmates 

were three times more likely to have been involved in pimping, while juvenile arrestees (9% of 

adult arrestees with a gang affiliation, 3% of those with no affiliation) while juvenile arrestees 

were 11 times more likely to admit to pimping than those with no affiliation (11% of juvenile 

arrestees with a gang affiliation, 1% with no affiliation) (SANDAG 2014).

The first local study to systematically interrogate gang involvement in sex trafficking was 

Carpenter’s Gangs: Regional Presence and Activity (GRPA) Project, which gathered information 

about gangs operating in San Diego and Tijuana and how they cooperated with each other. Using 

a list of penal codes associated with human trafficking offenses, GRPA documented the number 

of human trafficking related arrests or citations in 2010/2011; delineated and then transposed 

gang territories over San Diego County maps; and consolidated the two datasets to produce GIS 

maps of crime incidence by gang territory.

Carpenter’s analysis revealed that in 2010-2011, the majority of San Diego sextrafficking related arrests and citations occurred primarily in one area of the city, El Cajon 

Boulevard. Known also as “the Blade” or “Switzerland”, El Cajon Boulevard was a “a free-trade 

zone” where gangs put aside their differences and even collaborate to prostitute young women 

and men. GRPA also documented empirical evidence of rival gangs cooperating for purposes of 

sex trafficking (Carpenter and Cooper, 2012). 

At that time, law enforcement officials in San Diego County believed that prostitution 

was the second most profitable business for gangs after drug dealing (Tintocalis, 2011). In 

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.
38

Morgan’s 2012 San Diego research on practitioners’ experiences with gangs and sex 

trafficking/pimping one local law enforcement detective noted that at least 90 percent of his 

pimping cases involve gang members or individuals associated with gangs. However, of the 17 

closed pimping investigation that Morgan analyzed as part of her study, six (35.5%) pimps were 

documented gang members, two (11.8%) were not documented gang members but were 

associated with a gang, and nine (52.9%) were not affiliated with any gang. Although not 

necessarily representative of all cases citywide or countywide, her analysis revealed that only 

about half (47.1%) of the cases had ties to gangs and gang membership (Morgan, 2012). 

In his landmark study of sex trafficking in neighboring Tijuana, Mexico, Sheldon Zhang 

(2010) found that according to his interviewees, organized crime (including street gangs) had not 

infiltrated into the sex industry. “Considering the pervasive violence in drug cartel struggles 

along the U.S.-Mexico border and cross-border human smuggling activities, it was surprising 

that criminal organizations had not infiltrated into the sex industry” (Zhang 2010). While there 

were claims from informants that “gangsters” were moving into the sex industry due to 

increasing crack downs on the drug trade, “With only two exceptions, all sex trade facilitators 

interviewed in this study seemed to conduct their businesses without any interference from 

criminal organizations (or at least their own business activities were unaffected by organized 

crime)” (Zhang 2010). 

If it is a hallmark of organized crime to “sell, and enforce, protection to those involved in 

an informal economy that is neither recognized nor protected by the legal market system,” given 

that prostitution is a regulated and legal business in Zona Norte (Tijuana’s Red Light District), 

Zhang concludes that “it is unclear to what extent protection from any underworld organization 

is needed in Tijuana’s red light district” (Zhang 2010). If this holds true for Tijuana, it does not 

hold true for Tijuana’s neighbor to the north, San Diego.

I.D. Action-Based Research and Community Collaboration 

As researchers we found great value for the sake of research and for the community in 

designing this research project as what Ernest Stringer calls an Action-Based Research project 

(Stringer 2014). Action-Based Research as Stringer (2014) defines it is best suited for social 

inquiry where one has difficult access to tangible reality, in our case hidden, illegal activities like 

sex trafficking and gangs. “Everything that social inquirers study depends on mental 

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.
39

constructions and mental interpretations...Inquirers do not “discover” knowledge by watching 

nature do its thing behind a one-way mirror; rather, it is rather created by the interaction of the 

inquirers with the “object” (construct) into which they have inquired” (xi). 

In 2011 Drs. Carpenter and Gates were asked to be the founding co-chairs of the 

Research and Data Subcommittee of the San Diego County Regional Advisory Council on 

Human Trafficking and CSEC. As a Peace and Conflict Resolution professor at the University 

of San Diego, Dr. Carpenter was originally asked to join the group in part for her skills in 

mediation and conflict negotiation, as early perceptual differences and tensions between 

stakeholders threatened to derail collaboration. Dr. Gates was originally asked to be involved in 

part because of his wide range of community networks across the social service, community 

activist/advocacy and faith-based initiatives through his work as Director of the Center for 

Justice and Reconciliation. In addition to the research role, as co-chairs of the Research and 

Data Subcommittee both Carpenter and Gates were called on often enough to be neutral voices 

and mediators in the community process that Assistant District Attorney Mary Ellen Barrett 

dubbed them the “Switzerland of our movement.”

The action-based nature of this project grew out of the community’s desire to understand 

the scope and the nature of gang involvement in sex trafficking so that they could apply this 

knowledge to better legal and law enforcement, social service and educational policies and 

procedures. This project was built on the strength of collaborative relationships and open access 

to shared (often proprietary) information that came along with the hard work of collaborating 

with and through the San Diego County Regional Advisory Council on Human Trafficking and 

CSEC. This group not only gave access to key data and population groups to be interviewed, but 

the data the project had access to and the questions we were able to answer became increasingly 

clearer by the input, perceptions and needs of a wide range of community stakeholders. These 

stakeholders gave key data to the project, helped interpret key data from the project, and asking 

key questions of both the methods and preliminary findings of the project to help guide findings.

From a research perspective, the partnerships we nurtured through our involvement in the 

San Diego County Regional Advisory Council on Human Trafficking and CSEC helped us 1) 

address research questions that are most pressing to those working to raise awareness, curb sex 

trafficking activity, intervene with gangs, and rescue/rehabilitate victims 2) gain access to 

databases and populations that in the case of sex trafficking research would otherwise have 

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.
40

remained hidden and 3) have the most likelihood of impacting public policy and infrastructure 

for positive change.

While there was a high level of collaboration with professionals, we also worked to 

maintain a professional distance when necessary for an independent perspective. For example, 

cooperation with San Diego’s Commission on Gang Prevention and Intervention has been 

indispensable for understanding and interpreting findings from our interviews with current and 

former gang members. While we relied on members of this Commission for early intelligence 

and to give feedback on early findings, we generally worked outside of the known networks of 

gang members connected to the Commission for our interviews. To the degree that our research 

worked independently of the networks established by those already doing work related to gangs 

we were able to add substantive insight into the law enforcement, social services and faith related 

groups who currently are the most knowledgeable and engaged actors related to gangs.

The collaborative nature of San Diego’s movement to address human trafficking, 

combined with the legitimacy conferred by funding from the National Institute for Justice, gave 

researchers on this project broad and trusted access to non-public data from a wide variety of law 

enforcement agencies in San Diego County, the Sheriff and the San Diego Police Department in 

particular. Through this level of access we were able to compare measurements and findings 

across jurisdictions, something that during the course of our research our regional law 

enforcement agencies were working to improve. The dialogue between our research team, law 

enforcement analysts and community based-researchers helped to develop greater insight and 

more refined empirical measures for each of our respective roles.

Due to the limited funding and the meager budgets of most social service agencies 

working with survivors of human trafficking, much like for academic researchers, it is not 

uncommon to find a more competitive rather than collaborative relationship between social 

service agencies in a region. We worked with eight social service agencies to standardize 

portions of their intake tool so that as researchers we could be more confident that we were 

comparing apples to apples when we received data about the survivors that entered each 

organization’s care. We found all of the social service agencies willing to set differences and, to 

a degree, difficult past relationships aside in order to collaborate on this project. The research 

raised debate about and helped to refine where in the intake process such tools are best 

administered. While still in process as of the writing of this report, the network of social service 

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.
41

agencies that collaborate under the Victims Services umbrella of the San Diego County Regional 

Advisory Council on Human Trafficking and CSEC are using this research to outline a 

regionally appropriate intake assessment tool. A broader coalition of social service agencies has 

developed and are even collaborating on the first combined funding proposals.

The most exploratory part of our research was the focus groups we conducted in 20 high 

schools across San Diego County, spread across Central San Diego, the South Bay, East County 

and North County. Drawn from a purposive sample rather than a random sample that would 

allow us to extrapolate the findings with confidence across the region, the scope of trafficking 

found related to school and school children was nonetheless surprising and demands a more 

systematic analysis of the sex trafficking activities related to our schools. Having identified what 

school officials think is happening at their schools, a strong follow up research project would be 

to collect data from the students themselves. 

The star administrator of San Diego’s school-based CSEC policy development and 

developer of the national schools-based protocols being used at the time of the publishing of this 

report, Jenee Littrell, helped to facilitate research access to three school districts and the countyrun schools for the purposes of this study. Growing from this relationship the researchers have 

been invited into the human trafficking curriculum and CSEC policy development for the San 

Diego Unified School District (the second largest school district in the state) as well as for the 

San Diego County Office of Education.

In part from mid-stream information coming from our study and our ongoing dialogue 

with school officials, San Diego county school are in the process of developing systems to roll 

out sex trafficking education first to all key staff members in county schools, then to students 

through locally and developmentally appropriate awareness curriculum at the student level. 

Informally our findings helped to identify which staff members on average were better informed 

on CSEC (e.g. counselors, campus security and upper level administrators) and pointed to the 

need for greater information on indicators (how to identify) and protocols (what to do once 

identified) to spread across all staff in all schools across the county. 

An important practice and outcome of this project has been the regular interaction of a 

network of regionally based researchers studying various aspects of human tracking. As cochairs of the Research and Data Subcommittee of the San Diego County Regional Advisory 

Council on Human Trafficking and CSEC, the study’s investigators hosted quarterly gatherings 

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.
42

of other university-based researchers, graduate students, law enforcement analysts, social service 

research experts and community-based researchers to 

a) aggregate and compare regional HT-related research, 

b) convene and assist HT researchers working in the region, 

c) facilitate the networking between practitioners and researchers, 

d) identify HT research funding for participating researchers and identify appropriate 

collaborators

e) improve public knowledge of the results of county-wide research related to human 

trafficking across multiple disciplines and sectors.

The San Diego County Board of Supervisors saw such value in the collaborative 

gathering of researchers we were modeling that they decided to fund what we called HTRADAR (Human Trafficking Research and Data Advisory Roundtable), i.e. the ongoing 

coordination of county-wide human trafficking research. In late 2015 HT-RADAR was 

showcased by San Diego County leaders to the statewide Blue Ribbon Commission on Human 

Trafficking run by the HEAT Institute. We encourage a call for private/public partnerships to 

continue and increase research funding to develop more detailed and more robust local and 

regional findings, but also for the regional coordination of these efforts to help improve the 

focus, efficiency and impact of such research efforts.

II. METHODS

II.A. Site Selection - San Diego County

 The data collection for this study was done in San Diego County, California. Early 

dreams for including Tijuana in the core of our analysis were set aside early on because of 1) the 

logistical challenges associated with making this fully a cross-border analysis, including 

limitations to data access in Tijuana, 2) the strong and relatively recent research published on the 

Tijuana sex industry by our colleague Sheldon Zhang (2010), and, most importantly, 3) the 

charge of the San Diego County Regional Advisory Council on Human Trafficking and CSEC to 

study San Diego County to the degree that can improve countywide policies and practices. 

However, a supplemental NIJ award permitted us to perform a social media analysis of armed 

groups in Tijuana, the main output of which was new information about transnational gang-cartel 

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.
43

networks.22 We incorporate this data from Tijuana only in places where it impacts our 

knowledge of the scope and nature of gang involvement in sex trafficking in San Diego County.

San Diego has a population of approximately 3 million in the County (1.3 million of 

which live in the City of San Diego), and is known by its three most dominant economic engines: 

tourism, the military and biotechnology. It is the eighth largest city by population in the United 

States, but also the third largest on the trans-Pacific West Coast with Los Angeles coming in first 

and Tijuana second. As a tourist, military, university and border town, San Diego County has a 

high level of short and long term in/out migrations and visitors. It is no wonder that tourism, 

particularly the hospitality industry, is booming. According to the traffickers we interviewed in 

this study, sex trafficking piggybacks the hospitality industry, and it does so for two reasons: (1) 

there is a high population of potential buyers - single (or otherwise) male populations proximate 

to other sexual services such as strip clubs and massage parlors, and (2) a context where there is 

a low chance of getting caught or paying significant penalties for buying sex.

 Sex buyers, facilitator tell us, come from all walks of life, and from the widest range of 

socio-economic background. They are of all racial and ethnic backgrounds and connect via the 

internet to find sex for hire anywhere from the hotels on Hotel Circle and the Convention Center 

to mobile brothels set up in private suburban neighborhoods and wealthy gated communities. 

Facilitators argue that they are providing a service to a market in high demand, and that most 

buyers believe it is a victimless crime. Sex trafficking is an illegal and now heavily penalized 

crime in San Diego County for which someone when convicted can be fined upwards of $1.5 

million dollars and spend a minimum of 10 years in prison if the victim was an adult, 15 years in 

prison if the victim was a child. While soliciting or prostituting a minor in California under 

Proposition 35 can now be prosecuted as a Human Trafficking case and carries stiff penalties, 

few buyers ask the facilitators we interviewed if the one they were buying was underage.

In 2005 San Diego’s District Attorney Bonnie Dumanis channeled federal funding for the 

County’s first human trafficking law enforcement coordination efforts to the North County AntiTrafficking Taskforce run out of the County Sheriff’s Vista Sub-station in partnership with North 

County Lifeline, a wrap-around services social services agency (California Department of 

Justice). This taskforce was principally a gathering of law enforcement officials working on what 

they called “collateral time” (i.e. overtime, not as a central part of their job), collaborating with 

 

22 2012-R2-CX-0028 Supplement 01

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.
44

one another and with special investigative monies from the grant for larger operations. Social 

workers, concerned clergy and citizens and researchers began to join the North County Taskforce 

meetings as resource persons to the law enforcement operations. Collaborative relations 

developed among the North County team, but were limited in geographic scope and limited by 

the relatively few resources there were for the “collateral investigations.” The Taskforce laid the 

foundation for greater attention to human trafficking investigations and arrests, and prosecutions 

out of the District Attorney’s office went from nine in 2009 to 46 in 2013 near the start of this 

study.23

II.B. San Diego County Regional Advisory Council on Human Trafficking and CSEC

Funding for the North County Anti-Trafficking Taskforce had run out by 2010 but the 

synergy between the law enforcement and other sectors working against human trafficking and 

for the sake of the victims continued. By 2011 County Board of Supervisor Dianne Jacob 

collaborated with Sheriff Bill Gore and District Attorney Bonnie Dumanis to encourage the 

group to broaden and meet as a working group that could advise the County on matters related to 

human trafficking. Thus was born what was to become the San Diego County Regional 

Advisory Council on Human Trafficking and the Commercial Exploitation of Children.24

 In the middle of this study, and a contributor to the progress of this study, the authors 

were a central part of coordinating and leading a community-wide summit that would lead to a 

county-wide assessment of what assets for addressing human trafficking currently exist in San 

Diego County, and what next steps the Advisory Council would recommend to the Board of 

Supervisors, the Sheriff and the District Attorney. Hosted by Point Loma Nazarene University 

on January 24, 2014, the midpoint of this study, the researchers assisted with a summit that 

eventually led to substantive proposals from seven different sectors across the county including 

Law Enforcement, Prosecution, Child Welfare, Victims Services, Education, Community and 

Research and Data. As of late 2014 the county established a new law enforcement taskforce 

coordinating the investigations and information sharing between 19 agencies working against 

 

23 District Attorney’s data from personal communication with Chief Deputy District Attorney Summer 

Stephan.

24 Drs. Carpenter and Gates were both participants in and witnesses to these developments. A fuller and 

more formal history of these developments is yet to be written and would be a strong contribution to other 

communities wanting to make substantive progress in this area.

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.
45

labor and sex trafficking. Trainings of schools staff and law enforcement personnel across the 

county has gotten off the ground and at the beginning of 2015 the County decided to fund the 

coordination and dissemination of human trafficking research from around the county (the 

central proposal from the Research and Data Subcommittee that the authors of this study 

continue to chair at the time of this writing).

 The study design below relies on the multiple data sources that grew to become available 

to us as we walked through the almost three years of unfolding access to new and richer sources 

of data. We combined qualitative and quantitative data from existing sources with interviews 

and focus groups data generated uniquely by our project for a fuller picture of the scope and 

nature of gang involvement in sex trafficking in San Diego County than we would have been 

able to otherwise gain.

II.C. Study Design: Triangulation of Data from Multiple Sources

The primary methodological strategy of this study was to mine existing data sources, and 

cultivate new primary data from actors with first hand experience. The three existing data 

sources we were able to mine included 1) Survey Data from a mandatory diversion program for 

first-time prostitution offenders, called Freedom from Exploitation run by referral from the City 

Attorney’s Office; 2) Victim Intake data from eight nonprofits who work with trafficked 

individuals; and 3) Arrest and Booking data from the San Diego County Sheriff's Department, 

and California’s Automated Regional Justice Information System (ARJIS).25 These existing data 

sources were non-public, and required MOUs with each coordinating agency. We then created 

two additional data sources previously untapped in San Diego 4) focus groups with staff from 

San Diego County high schools, and 5) extensive interviews with individuals involved with or 

directly knowledgeable about sex trafficking. The following section describes the research 

methodology in detail. 

II.D. Data Collection 

 

25 According to the ARJIS’s homepage, the system “was created as a Joint Powers Agency to share 

information among justice agencies throughout San Diego and Imperial Counties [and] has evolved into a complex 

criminal justice enterprise network used by 80+ local, state, and federal agencies in the two California counties that 

border Mexico.”

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.
46

II.D.1. Survey Data from Freedom from Exploitation (FFE)

Freedom from Exploitation (FFE) is the name of a diversion program offered to all 

individuals arrested for their first offense of PC 647b (Prostitution). Kathi Hardy is a social 

worker who runs FFE, and another diversion program for minors at the Girls Rehabilitation 

Facility (GRF), one of San Diego County’s Juvenile Detention Centers for minors. Since 2005, 

Hardy had been gaining permission from her clients to aggregate their data for research purposes 

and administering extensive surveys with questions that remained constant, exploring the 

participants’ life histories. She therefore had collected a robust sample of survey data from 702 

individuals arrested for PC 647b (Prostitution) for an 11-year period. We analyzed Hardy’s 

existing data, and requested that she incorporate questions from our project’s standardized 

Trafficking Victims Intake Tool (discussed further below) for the duration of the study for the 

sake of comparison.

II.D.2. Victims Intake Data from Eight Social Service Providers (SSP8)

Most studies of trafficking victims are based on studies of victims who get assistance in 

shelters or other assistance programs. However the indicators used to determine presence of 

human trafficking are not consistent across social services agencies, and may not overlap with 

current standardized legal or research terminology (Brunovskis and Tyldum, 2005). Our study 

introduced a standardized screening tool for use in San Diego social service agencies for the 

duration of the project. Given the robust validation methodology behind the screening tool 

developed by the New York City Trafficking Assessment Project or NYCTAP (Simich, Goyen 

and Mallozi, 2012), the research team chose to pilot the its tool with area service providers. The 

tool is called the Trafficking Victims Identification Tool (TVIT).

The TVIT was developed by the Vera Institute of Justice, and we received permission 

from its authors to use the tool in this study. For our purposes, we used an abbreviated version of 

the tool consisting only of Sections 2 (Personal Background), Section 3 (Migration), and 5 

(Living and/or Working Conditions). We also adapted the TVIT to include questions about gang 

involvement. Eight (8) providers each agreed to pilot the Trafficking Victims Identification Tool 

during their intake process.26 We refer to this data in the aggregate with the acronym SSP. The 

 

26 The Victims Services Subcommittee identified 173 organizations in San Diego County that provide 

resources for victims of human trafficking. With a total population of 173, we strategically targeted those agencies 

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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.
47

service providers also agreed to permit the research team to retrospectively code their interview 

data extending backwards. Ultimately three methods were used, as shown in Table 1 below. 

Table 1: TVIT Implementation

Method n (%) (Total n = 207)

Direct interview with client 28 (13.5)

Retrospective- previous intake 122 (58.9)

Retrospective- previous intake & staff recall 57 (27.5)

II.D.3. Arrest and Booking Data from Law Enforcement Agencies

We used the Law Enforcement Dataset to estimate the number of CSEP and CSEC that 

law enforcement had come into contact with between 2007-2014. The aim was to identify arrests 

in which at least one victim of Commercial Sexual Exploitation could be identified. Our original 

thought was to combine prostitution arrests with arrests for California’s 12 Human Trafficking 

Predicate Crimes, for a better estimate of total commercial sexual activity (CSA) encountered by 

law enforcement. In addition to penal codes 236.11 (Human Trafficking) and PC 236 (False 

Imprisonment), the State of California has established that the following 10 penal codes are 

Human Trafficking Predicate Crimes, crimes closely associated with trafficking in persons 

(Gascon, 2013): 

We concluded that using all 12 of these penal codes as proxies for sex trafficking would 

have created an over-estimate of victimization for two reasons. First, unless one looks through 

the associated arrest records and field notes, some of these penal codes are not what they 

appear.27 The city of Chula Vista in southeast San Diego County did look through all of their 

arrest records, in order to illustrate this point. They found that all incidents of 311.1A (Intent to 

 

that work explicitly with trafficking victims. We were able to establish partnerships with eight out of a total of 10 

organizations that work explicitly with trafficking survivors. 

27 This research is deeply indebted to the city of Chula Vista for generously agreeing to examine by hand 

all of the arrest records for the penal codes above. Melanie Culuko is the Public Safety Analyst who conducted this 

research by going through each arrest record, and we are incredibly grateful for her work identifying the penal codes 

and cases that represented actual cases of human trafficking predicate crimes. After Culoko’s analysis, the initial 

number of incidents reported (557) was reduced to 159. 

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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.
48

Distribute Child Pornography) were cases in which teenagers had broken up, and the exboyfriend had texted nude pictures of his ex-girlfriend to the boys in his contact list. All cases of 

288 (Lewd Acts with a Child) were incidences of child molestation within a family, or by a 

teacher. Likewise, extortion charges had nothing to do with sex trafficking. Since we could not 

duplicate this level of analysis with the much larger countywide dataset, we dropped Penal 

Codes 518, and 288 to err on the side of caution. We also excluded child pornography (311.1-6) 

because, in our view, counts of this crime do not contribute to estimates of sex trafficking. We 

also curtailed our use of 236, discussed further in Section III.C.2. 

Table 2. Human Trafficking Predicate Crimes

266 Enticing minor for prostitution/sex

266a Take prisoner to prostitute

266h Pimping

266i Pandering

266j Transporting or making available for sex a minor

267 Taking minor from legal guardians for prostitution

288 Lewd Acts with Child

311.1-6 Child Pornography

518 Extortion

653.23 Supervising Prostitute

A second part of the Law Enforcement dataset emerged several months into the study. 

Our law enforcement partners consistently recognized that their current trainings and procedures 

likely undercount the level of victimization due to lack of training of personnel, recent 

introductions of new laws and the lag time in integrating this into policy and practice, wide 

variation in officer knowledge, etc. A consistent theme from field officers and agents was the 

strong connection between domestic violence cases and potential sex trafficking incidences. So, 

we asked that a key word search be performed on the field notes of Sheriff Department data to 

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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.
49

look for signs of sex trafficking in the Domestic Violence incident reports as a means of 

estimating under counting in the current law enforcement procedures. 

II.D.4. Focus Groups in San Diego County High Schools

Focus Groups were conducted with staff from county high schools to learn about reported 

and suspected incidents of high school students being recruited for or engaged in commercial 

sexual exploitation; to gain insights from staff into gang activity and recruitment vulnerabilities; 

to understand staff awareness of human trafficking and to gain insight into what next steps 

schools would need to address awareness and action related to CSEC. Our project developed a 

Memorandum of Understanding (MOU) with the San Diego Unified School District (SDUSD), 

Sweetwater School District (SSD), one high school in the Grossmont Unified School District and 

the San Diego County Office of Education. We conducted focus groups across 20 high schools 

with a total of 141 school staff members, including administration, teachers, counselors, social 

workers, nurses, police/safety personnel and other campus program staff, with on average 

approximately 7 persons per focus group. 

After gaining permissions from the District research offices/personnel, district 

administration made principals aware of the research project and requested participation. We 

contacted schools across each district, but placed a priority placed on schools that register high 

on self-reported gang involvement by student on the California Healthy Kids Survey. While the 

highest concentration of schools were in the central part of San Diego, we sampled from North 

County, Central County, East County and the South Bay. Schools represented the full range of 

socio-economic diversity in their populations and geographies.

In our content analysis of the school focus groups we went through each school focus 

group transcript coding for factors associated with CSEC victimization or recruitment, listed 

each emergent factor (e.g. “financial problems/need or want money”) and the school number 

associated with the staff comment. We combined same/similar factors together and created 

organizing categories. We eliminated factors not represented in more than one instance to 

tabulate a summary of the most important factors that staff considered to be important in the sex 

trafficking recruitment they observed on their campuses

II.D.5. Individuals Involved with or Knowledgeable about Sex Trafficking

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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.
50

A significant portion of this study was designed to obtain information about the sex trade 

from incarcerated individuals in San Diego County as well as individuals not incarcerated but 

connected to gangs and sex trafficking directly. The ethnographic method of in-depth interviews 

with community-based and incarcerated gang members was purposefully selected because of its 

efficacy in other studies of non-state armed actors and their relation to larger societies, including 

studies of rebel militias in Sierra Leone (Hoffman, 2007), slave-traders in Sudan (Jok, 2001) 

warlords in Afghanistan (Coburn 2010), and youth gangs in Chicago, Rio de Janeiro, and Kenya 

(Hagedorn, 2012). The epistemological assumption shared between these studies and ours is that 

insider perceptions are critical to learning about how such groups operate. While there are 

important reliability and validity concerns to take into consideration when relying upon the selfreports of these accounts, given the hidden nature of this phenomenon, insights from a group of 

active or former offenders using this approach is invaluable (Watters and Biernacki, 1989).

We conducted in-depth interviews (IDIs) with individuals who were involved in or 

knowledgeable about pimping/trafficking. We pursued two subsets: (1) local law enforcement 

gave us access to 139 inmates (124 male, 15 female) held in Protective Custody (PC) in local 

detention facilities and (2) we were able to grow a snowball sample of 15 current/former 

facilitators in the community. In both cases, our original goal was to target individuals who were 

documented members of certain gangs that the GRPA project had documented as being involved 

in trafficking activities. However, we decided early on to open up the study to all inmates in PC 

who wished to participate. 

Our reasoning was twofold. First, several of the groups identified in the earlier GRPA 

study were not reported to be present in San Diego detention facilities. Law enforcement partners 

expressed their difficulty with identifying and documenting gang membership, and suggested 

that we should not limit our sample based on their records. This turned out to be prescient; as 

discussed further on, the majority of gang members we encountered had not been identified by 

law enforcement, but rather self-identified to the researchers during interviews. Our sampling 

method was therefore non-purposive: in order to represent the population of prisoners as nearly 

as possible, prisoners were not screened for gang involvement, mental status, or charges. 

All interviewees were from PC to minimize the perception of 'snitching' and the 

propensity for violence on the mainline. That was the only inclusion/exclusion criterion. The 

classification deputy at each facility made an announcement into each cell asking if the inmates 

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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.
51

were interested in participating in a university research study. Those that wished to participate 

were brought to the interviewer. Participation was voluntary and inmates had to self-select/opt-in 

to the process. The deputy had anybody interested in participating sign up during a previous 

work shift, in order that we would have a sample to pull from the day of the interviews. 

As we averaged 4-5 interviews per day, there were virtually always more people 

remaining on the list for the following interview week. Thus, the deputy did not need to ask each 

individual about their willingness to participate, rather only had to randomize the sample of optin names s/he had on hand. Once the interviewee a) opted-in and b) was randomly chosen from 

the opt-in list to participate, that individual was brought to the private interview room. We did 

not know anything about the inmate pool until an inmate physically walked into the interview 

room. The interview occurred in a room usually used for “professional” (legal) visits. Thus, 

interviewers did not know whom they were interviewing. They immediately informed each 

person walking into the room that they did not know their name or booking number in order to 

assure participants that everything said remained confidential.

For the 15 un-incarcerated individuals we interviewed, we initiated our snowball sample 

through our existing contacts and attempted to recruit gang-involved individuals believed to have 

knowledge about or experience with pimping/sex trafficking. We gained access to this 

community-based convenience and snowball sample through: (a) former gang members still 

connected to the streets (often through their work with churches/ministries, gang outreach 

programs, re-entry programs, drug treatment facilities) (b) other intermediaries (pastors and other 

trusted community members) who have relationships with current or former gang members 

working as pimps/traffickers, and are willing to refer us to them for an interview and (c) referrals 

from gang-related traffickers we already interviewed.

For both sets of interviews, we used an interview protocol inspired by Zhang’s (2010) 

trafficker interview protocol, but developed specifically for this study (see Appendix A). Our 

protocol included detailed questions/prompts about whether, how, and to what extent the gang 

facilitates and/or plays a role in trafficking/pimping activities; whether the individuals involved 

from one gang/group cooperate with other gangs/groups and how that works; the nature and 

extent of their involvement in other criminal activities; and their awareness and perceptions of 

the possible consequences—criminal sanctions and sentences—for their involvement in sex 

trafficking/pimping.

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.
52

We also included a measure to ensure that we understood when interviewees were 

providing provided reliable information. Two list experiments were included in the interview 

protocol, which tested for bias effects on two "sensitive" questions. These tests were used to 

gauge an individual’s comfort level in admitting involvement in pimping or having sex with 

prostitutes. The results of the analysis indicates that the people were generally truthful, and that 

the actual incidence of facilitation is roughly 66-78% higher than people report in response to the 

initial list question, which has methodological implications for future studies. We discuss this 

further in section III.C.2.

An important methodological consideration is that approximately 2/3 of sex trafficking 

facilitators in this study did not identify themselves by the word ‘pimp’. We did not know this 

when we created the list experiment questions, one of which was “I have pimped out one or more 

girls before”. When we realized that ‘pimp’ was viewed as a social identity, not a verb, we 

changed the language in our questionnaire. The following excerpt of one transcript illustrates the 

delicate nature of getting the wording right, and probing for accurate responses.

Interviewer: Has a prostitute ever paid you for a particular service of any kind?

Respondent: Yes. 

Interviewer: Have you yourself been involved in pimping out a girl, or any girls?

Respondent: No. 

Interviewer: So when you said yes, has a prostitute ever paid you for any particular service? 

Could you fill me in a little bit?

Respondent: I mean, they would just make sure, they would just ask me, ‘Hey, if I give you 

this money could you make sure that I come back from where I was at?’

It wasn’t me saying, hey you gotta go out there and do this. They were like, ‘Hey, 

I’m doing this right now could you sit there and make sure that I come back 

outside that room or that there’s not weirdos trying to beat them up or something.’ 

A lot of guys that go into places like that, some guys are fetishing, it’s weird. It’s 

not cool from my perspective but I mean I was just a friend trying to help them 

out and they were like hey, this is what I’m doing. I was like a little brother to 

them trying to make sure they were ok. Because they were already doing it. I just 

didn’t want them to get hurt. Because you know how I’d became friends with 

them.

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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.
53

Interviewer: Making sure they were ok?

Respondent: Yeah. 

Interviewer: So almost like a security guard of some kind?

Respondent: Yeah. 

II.E Study Design Limitations

Methodological limitations are associated with each source and method of analysis. This 

section regards methodological challenges to use of the TVIT, consolidating law enforcement 

data, research in schools, and in-depth interviews (IDIs) with trafficking facilitators.

II.E.1. Trafficking Victims Identification Tool (TVIT)

Two methodological challenges presented themselves with regard to the efficacy of the 

TVIT for our specific purpose: identifying gang affiliation of traffickers. First, trafficked 

individuals are uncomfortable identifying whether or not their trafficker was gang affiliated. 

When the tool was used in person (most often by Kathi Hardy during the mandatory FFE 

meetings), we found that individuals were very uncomfortable answering this prompt because it 

felt like ‘snitching’. Individuals were more likely to name gangs in the abstract (in response to a 

prompt like “Which gangs do you know of that are involved in pimping?”) as opposed to direct 

questions (“Was your pimp/trafficker part of a gang/clique/set/crew?”). 

Second, a majority (103) of the 170 survivor intake forms were coded retrospectively, 

and the individual performing the original intake usually did not ask whether or not the trafficker 

was gang affiliated. Therefore we believe there is underreporting of gang-involved traffickers in 

the Victim Service Providers data set. 

II.E.2. Law Enforcement Incident Data

The primary methodological challenge was that prior to 2007, law enforcement agencies 

did not collect and store identifying information using the same format. We wished to go back as 

far as 2001 to count the number of arrests for Human Trafficking Predicate crimes, but doing so 

meant gathering individual records from the San Diego County Sheriff’s Department, and 

eighteen police departments. We compensated for this by analyzing bookings into County Jails 

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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.
54

regardless of the arresting agency, provided to us by the Sheriff’s department. This dataset went 

back to 2001. In 2007, the County launched the Automated Regional Justice Information System 

(ARJIS), created as a joint powers agency to share information among justice agencies 

throughout San Diego and Imperial Counties, California. ARJIS provided us with arrest data 

from January 2007 to June 2014. 

Even with this system, we encountered two challenges: (1) multiple individuals arrested 

under one case number, giving the appearance of duplicates (raising the risk that one might 

delete what looks like a duplicate but is, in fact, a unique individual case) and (2) persistent 

differences in how Sheriff's Department lists arrests versus other agencies. The Sheriff’s 

Department appends the end of the case number with a 01, 02, 03, etc. based on the number of 

individuals arrested in that case (ex. 1000639101 & 1000639102 and 1115019601 & 

1115019602). This delineates multiple individuals arrested under the same case number. 

However there is a catch: the first adult arrested in the case gets a 01 at the end of the case 

number AND the first minor arrested in the case gets a 01 as well. 1212798801 & 1212798802 

are examples of this caveat. 12127988 is one case with 4 individuals arrested. Without being able 

to pull the case data, looking for duplicates was therefore tricky, requiring frequent 

communication with law enforcement partners.

II.E.3. School Focus Groups

Three methodological challenges presented themselves with regard to school focus 

groups. First, given the sensitive nature of the topic, some schools wished not to participate. 

Even so, the rate of participation was tremendously high and the San Diego County Board of 

Education gave their consent for the research team to approach high schools at will. 

A second challenge is that there is no consistent definition of “reported” incidents – some 

cases are reported to staff by law enforcement, others by students or parents, and some by fellow 

staff. There existed some variance between specific cases described when question #1 was asked 

(“Are you aware if there are incidences of girls and/or boys being recruited for commercial 

sexual exploitation here?”) and when question #4 was asked (“How many victims did you 

personally come into contact with?”). 

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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.
55

Perhaps most importantly, there existed a wide variation of focus group participant 

awareness and training on human trafficking, and therefore the validity of the perceptions 

reflected in the data is conditions by this wide variation.

II.E.4. In-depth Interviews with Incarcerated Individuals

A key limitation was our inability to accurately assess the non-participant pool, for 

multiple compounding reasons. First, all three county jails are very dynamic places. A 

combination of arrest dates and sentencing dates meant that individuals interviewed had been 

incarcerated in that particular facility for as short as a few hours and as long as a decade or more. 

Individuals facing sentences for more violent crimes were more likely to be transferred to state 

prisons upon sentencing. Thus, an inmate who may have been present and willing to participate 

in the study may have been transferred to another facility by the time their name would have 

been randomly drawn by the deputy. 

Table 3 below shows the approximate total population in PC at the time of interviews for 

each facility, the number of inmates interviewed at each facility, the number of inmates who 

wished to participate but could not because we ran out of time (approximately 4-5 per day, 

according to the deputies we worked with), and the number of inmates who refused (meaning 

they signed up, but decided not participate after seeing the consent form). 

Table 3: Approximate In-Depth Interview (IDI) Response Rate 

Facility Average Total 

Population in PC

Inmates 

Interviewed

# Inmates Refused or 

Withheld 

Participation

George Bailey Detention Facility 314 53 n/a

San Diego Central Jail 8028 69 1

Los Colinas Women’s Detention 

Facility

21 15 6 

(1 refused, 5 others 

were present but did not 

 

28 Daily averages for PC inmate population by month: 9/14-(77) 10/14-(77) 11/14-(72) 12/14-(74) 1/15-

(89) 2/15-(90), as reported by the Crime Analysis division of the San Diego Sheriff’s Department.

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.
56

opt in.)

Of the 139 interviewees brought to the interview room, a total of two interviewees 

refused to participate further once the consent form was explained to and read by the inmate. 

One such incident occurred at Las Colinas and one at Central. Both cited the nature of the study, 

which hit too close to home in terms of personal experience and sexual trauma. Both inmates 

were white/Caucasian, and their approximate age was late 20s or early 30s.

Further, given the limitation of only being allowed to interview protective custody 

inmates, that population was additionally dynamic if any individual chose to leave the mainline 

cell blocks in order to join the PC population. That dynamic is a one-way street, as PC inmates 

do not re-join the mainline. 

Additional general challenges associated with this method are as follows. First, being 

restricted to PC for interview sampling meant we only interviewed certain inmates who had 

already ‘debriefed’ – it’s possible we missed those facilitators who were more integral to gang 

and/or facilitation activity because they were on the mainline and incentivized not to drop-out. 

Second, inmates opted-in to the study, meaning we may have biased our sample towards a) those 

wanting to talk and/or b) those incentivized by the monetary compensation involved with the 

study. The opt-in may mean that we missed significant and/or important populations who chose 

not to participate (refugees, Asian/Asian Pacific Islander communities, or those with relevant 

backgrounds fearing they could not trust us). 

The non-purposive sampling within the PC context also meant we interviewed multiple 

people who had no idea of and/or involvement with trafficking facilitation. This took up 

significant time and resources that could have been devoted elsewhere. However, pre-screening 

individuals would have likely let many interviewees fall through the cracks, as inmate selfreported gang affiliation was much higher than the Sheriff’s classification system.

A third issue had to do with verification of facts. In certain cases, the interviewer 

suspected or intuited embellishment or something amiss in the interview. We could not control 

for and/or deal with that without the ability to independently verify their story (due to deidentified nature of the interview structure). As noted earlier, the list experiments included in the 

interview protocol were meant to control for this issue. 

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.
57

An additional challenge was our lack of follow-up ability – certain interviewees didn’t 

want to speak on tape about the details of operations, and opted to speak in more general terms 

about their environment or what they generally know, rather than what they participated in 

directly. We also didn’t know if particular inmates had ‘beef’ with the deputies utilized to 

facilitate this study, or if the deputies may have passed over particular individuals due to strained 

relationships within the penal system. We were told selection was random, however we have no 

way to verify this at the moment, and must take the deputies at their word. 

Finally, the diverse nature of San Diego, and of the inmate population, may make 

projections difficult – from Mexican Mafia members to homeless methamphetamine addicts and 

white supremacists to homosexual black sex workers, the range of incarcerated interviewees was 

vast. Additional challenges associated with community interviews (with non-incarcerated 

individuals) primarily centered around the significant time it took to build the trust and 

relationships required to access current gang members.

III. FINDINGS AND ANALYSIS

This section reports quantitative and qualitative findings that shed light on the scale and 

complex challenges associated with gang involved Commercial Sexual Exploitation of People 

(CSEP), Commercial Sexual Exploitation of Children (CSEC), and Commercial Sexual Activity 

(CSA) broadly defined (see Appendix B for a Glossary of terms). 

III.A. SCALE OF THE UNDERGROUND SEX ECONOMY IN SAN DIEGO

We estimate the size of the illicit sex economy for 2013 in San Diego County at $810 

million dollars. We reached this number by duplicating - with two changes - the methods used by 

the Urban Institute to estimate the size of the underground sex economy in San Diego California 

in their 2014 study. The decision to do so was based on (1) appreciation for the sophistication of 

the methods employed by the Urban Institute and (2) our desire to replicate the design using the 

robust qualitative data generated by this two-year study. 

First we generated an estimate of total cash stock in San Diego. We began by modeling 

the cash-to-GDP ratio for the United States on a quarterly basis since 1959. We then used the 

model to make adjusted predictions of cash-to-GDP ratios for San Diego with all predictors set at 

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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.
58

levels reported for the metropolitan statistical area (MSA) of San Diego by the Bureau of 

Economic Analysis (BEA).29. We then multiplied the cash-to-GDP ratio by the GDP for the 

metropolitan region. The resulting cash-to-GDP ratios and total cash stock estimates for San 

Diego are presented Table 1 below, which also lists the comparable estimates as reported by 

Dank et al. (2014). 

Where we have comparable data (i.e., 2003 and 2007), this study’s estimates greatly 

exceed those of Dank et al. (2014). It is difficult to say where the discrepancy lies exactly. First, 

the models do not yield the same coefficient estimates, although their r-squared statistics are 

similar. For instance, the coefficient for per capita real GDP is reported by Dank et al. (2014) to 

be positive, whereas we find it to be negative. Indeed, a negative coefficient in some sense makes 

more sense: wealthier individuals tend to use bank transfers, credit cards, and checks more than 

cash, and high-value goods are usually not sold in cash. 

Second, Dank et al. (2014) also report “naïve estimates” of the M1 cash stock in San 

Diego that are almost identical to their regression-generated estimates. They do not expound on 

this point, but it is difficult to see how they came up with those figures; we recreated the 

calculations and obtained much higher estimates in the same fashion. We also back-calculated 

implicit cash-to-GDP ratios from the total M1 cash estimates reported by Dank et al. (2014) by 

dividing their estimates by the metropolitan GDP for that year (see column 4 of Table 4). We 

found them to be quite low compared to the national averages. 

This second set of discrepancies (i.e., the results) might be explained if Dank et al. (2014)

had used a more restrictive geographic definition of San Diego – for instance the city boundaries, 

as opposed to the Bureau of Economic Analysis-defined Metropolitan Statistical Area. However, 

BEA data are available at the MSA level. It is unclear what sources were used to adjust the 

model. Moreover, that explanation fails to explain why the OLS models – both based on the 

same FRED data – did not yield identical coefficients. In brief, it may be that Dank et al. (2014)

considerably underestimated the size of the cash stock in San Diego, which likely biases 

downward their estimates of the illicit sex economy, as well. 

 

29 We are able to find MSA-specific data on all predictors save corporate profits as a percentage of GNI and 

the GDP inflation rate. The latter is a national statistic anyway. Both were therefore set to year-specific national 

averages. 

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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.
59

Table 4: Cash-to-GDP Ratios and Total Cash Stock Estimates for San Diego 

After generating cash stock, we created proxy variables for each of the four suggested 

components of the cash economy using principal components analyses (PCAs). For the sex 

industry, we used the first principal component of a PCA of numbers of victimization incidents 

and number of perpetrator incidents related to sex trafficking in the San Diego County Sheriff’s 

Department database from 2003-2013 (with imputed numbers for 2000-2002). For the illicit 

drugs market, we used a PCA of the percentages of various categories of arrestees testing 

Cash-to-GDP Ratio Total Cash (US$b)

Year

Study 

Estimate

National

Avg.

Implied Dank

et al. (2014) 

Estimate Study Estimate

Naïve

Estimate

Dank et al. 

(2014) Estimate

2001 0.067 0.087 9.81 12.827

(0.053, 0.079) (7.801, 11.629)

2002 0.064 0.093 9.87 14.408

(0.050, 0.077) (7.758, 11.947)

2003 0.063 0.095 0.048 10.24 15.285 7.79

(0.050, 0.077) (8.071, 12.429)

2004 0.063 0.097 10.57 16.374

(0.049, 0.076) (8.284, 12.849)

2005 0.0634951 0.097 11.13 17.027

(0.049, 0.078) (8.59, 13.674)

2006 0.0689642 0.095 12.30 16.929

(0.056, 0.082) (9.986, 14.622)

2007 0.072 0.093 0.047 13.06 16.772 8.49

(0.060, 0.084) (10.829, 15.161)

2008 0.083 0.093 14.95 16.707

(0.072, 0.094) (12.94, 16.894)

2009 0.093 0.110 16.13 19.064

(0.082, 0.104) (14.232, 18.051)

2010 0.107 0.116 18.53 20.178

(0.097, 0.116) (16.837, 20.135)

2011 0.113 0.126 20.08 22.482

(0.104, 0.121) (18.566, 21.601)

2012 0.118 0.145 21.66 26.522

(0.111, 0.126) (20.307, 23.052)

2013 0.121 0.159 22.53 29.595

(0.115, 0.128) (21.402, 23.822)

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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.
60

positive for any drugs, marijuana, methamphetamines, cocaine, and opiates, as well as a few 

related statistics. For the illicit guns market, we use a PCA of the imputed dollar volume of guns 

sold “above board” (as derived for the study by McDougal, Shirk, Muggah, and Patterson 

(2014)), an estimate of 5-year licit stocks in private hands derived therefrom, and the percentage 

of suicides committed using a firearm. 

For all other legal cash industries, we considered BEA-reported revenues from five 

possible industries: construction, food services, retail, gambling, and private services. We were 

unsure which of these should be included in the final PCA. We therefore created principal 

components for all three-industry combinations of those five, plus one combining all of them 

together. We also included a standardized variable for the population of the county, presuming 

that number of people is a much better proxy for cash spent on legal goods and services than 

total personal income (since wealthy people tend to use credit cards and checks more, but still 

spend some relatively small amounts in cash). The population cash proxy was included on a 

separate basis in the model. 

Finally, we ran OLS regression models of total cash on all of the PCA components, 

forcing the models to drop the constants. This is because we want to force the model to estimate 

the amount of cash based solely on those four components, without any wiggle room (see Table 

5). 

We deemed that the most appropriate model would meet two basic criteria. First, all 

coefficients therein would be positive. Second, the licit cash economy should represent over 50% 

of the total cash economy. 

By these criteria, Model 2 is the only acceptable one, which generally agrees with the 

choice of Dank et al. (2014) to include the construction and food services industries, but also 

adds in recreation and gambling – industries that intuition might naturally associate with cash 

spending. Multiplying the coefficients by the PCA variable values, we arrive at estimates of each 

component of the San Diego cash economy (see Figure 1). 

Many of these values seem a priori quite high. There are many possible reasons for this. 

For starters, our proxy variables for the illicit firearms markets are probably not strong, as they 

deal primarily with the licit market and stock of arms. This alone might greatly affect our 

estimates. We asked the US Bureau of Alcohol, Tobacco, Firearms and Explosives for data on 

illegal seizures, straw purchasing, or other variables that could better serve as proxies for the 

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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.
61

market but did not receive this information prior to the study’s end date. Also, our proxy 

variables are generally likely to capture variations in the licit and illicit cash economies of related 

industries. It may even be the case that they pick up indirect and induced effects of illicit 

purchases in the cash economy. In that case, our estimates would be exaggerated by some 

“multiplier effect.” For instance, the National Shooting Sports Federation (NSSF, 2015) 

estimates that the gun industry’s economic multiplier effect is about 2.4.

Table 5. The Four Modeled Sectors and their Composite Variable Proxies with Sources 

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62

Sector Variable Source

Illicit Sex Sex trafficking victimization charges San Diego County Sheriff’s

Department booking records

Sex trafficking perpetrator charges San Diego County Sheriff’s 

Department booking records

Illicit Drugs Arrestees + for any drug, juvenile (%) Burke (2014b)

Arrestees + for any drug, adult males (%) Burke (2014a)

Arrestees + for any drug , adult females (%) Burke (2014a)

Arrestees + for marijuana, adult males (%) (Burke, 2014a)

Arrestees + for marijuana, adult females (%) (Burke, 2014a)

Arrestees + for methamphetamines, adult (%) (County of San Diego 

Methamphetamine Strike Force, 2004, 2009, 

2014)

Arrestees + for methamphetamines, juvenile (%) (County of San Diego 

Methamphetamine Strike Force, 2004, 2009, 

2014)

Meth arrestees claiming the drug is easy to 

obtain (%)

(County of San Diego 

Methamphetamine Strike Force, 2004, 2009, 

2014)

Arrestees + for cocaine, adult males (%) (Burke, 2014b)

Arrestees + for cocaine, adult females (%) (Burke, 2014a)

Arrestees + for opiates, adult males (%) (Burke, 2014a)

Arrestees + for opiates, adult females (%) (Burke, 2014a)

Illicit Guns Imputed guns sold legally in SD (McDougal et al., 2014)

Imputed licit 5-year gun stock in SD (McDougal et al., 2014)

Suicides committed by firearm (% of total) (Wagner, 2013, p. 90)

Other Construction sector regional product (US$b) (Bureau of Economic Analysis, 

2015)

Food sales sector regional product (US$b) (Bureau of Economic Analysis, 

2015)

Retail sector regional product (US$b) (Bureau of Economic Analysis, 

2015)

Recreation and gambling regional product 

(US$b)

(Bureau of Economic Analysis, 

2015)

Private services regional product (US$b) (Bureau of Economic Analysis, 

2015)

Population (inserted separately)

Still, there are two reasons to give these estimates credence. First, the estimates for the 

drug economy eclipse those of the sex economy (which is not true in the case of the Dank et al. 

(2014) study). Whilst large illicit drug seizures are more typically made in the US-Mexico border 

areas of Arizona and southern Texas, San Diego and Imperial Counties do figure prominently in 

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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.
63

drug seizure data from the US Border Patrol, in terms of marijuana, cocaine, methamphetamine, 

and heroin. It is therefore reasonable to presume that San Diego has a large drugs market relative 

to its population. (The same might, of course, be true of San Diego’s position in the sex and 

human trafficking markets.) 

Figure 1. Estimated sizes of components of the San Diego County cash economy, 2000-2014. 95% confidence 

intervals are displayed as whiskers. 

Second, the higher estimate seems to square with the higher-than-expected prevalence of 

sex trafficking in San Diego. 33% of sampled individuals in protective custody self-identified as 

sex-trafficking facilitators. In other words, 33% were currently or had been directly involved in 

facilitating CSA and/or CSEP. This finding suggests a high prevalence estimate, when coupled 

with the fact that most facilitators are not currently incarcerated and that there are multiple 

victims per facilitator (discussed in more detail in Section III.C.2). An even higher percentage of 

interviewees - 68% (95) - reported that they had friends or associates that were facilitators. 

Knowledge of commercial sexual activity was therefore extremely widespread within the 

-5.00

0.00

5.00

10.00

15.00

20.00

25.00

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Market in US$ Billions

Year

Sex Industry Drugs Markets Guns Market Other

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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.
64

population of inmates we interviewed; only 32% of inmates interviewed had no knowledge of 

and/or involvement with facilitation. 

These findings are suggestive that CSA pervades the criminal subculture of the region. 

Interviewees were in general consensus on this point; respondents told us that ‘pimping’ is not a 

stand-alone gang activity, but rather accompanies an array of other illicit activity, especially drug 

sales and use. These behaviors/activities are typically co-occurring. Addiction is intertwined with 

protector and prostitute roles; several facilitators described both they and “their prostitute” as 

“dope fiends” and the prostitution as a means for acquiring drugs. 

The finding that prevalence of sex trafficking is high in San Diego confirms what law 

enforcement and victim service providers suspected. However, the specific dynamics of how the 

gang involvement in sex trafficking was uncharted territory. 

III.B. FACILITATORS

Our interviews with incarcerated individuals strongly suggest that gangs in San Diego are 

engaged in the commercial exploitation of people and children (CSEP and CSEC). We identified 

33% (46 out of 139) of those interviewed as sex trafficking facilitators, and nearly 80% (37/46) 

of those facilitators affiliated with a gang. Over half of the inmates in our sample (57%) had not 

been identified by law enforcement as being gang affiliated, but disclosed their gang membership 

over the course of the interview. Another 34.5% were both identified both by previous law 

enforcement records, and through self-disclosure during the interview.

In all, we interviewed 56 self-identified facilitators (46 in jail and 10 in the community), 

and fourteen (25%) denied any gang affiliation. Examples of facilitators in the 25% not affiliated 

with any gang also include

● A Homeless Individual: ”...they called him ‘Grandma,’ and he was in Balboa Park, and 

he was kind of a pimp. He was like 50 something and he had a bunch of boys that he 

would hustle around the park” (Interview 77).

● A Parent: “I’ve seen somebody sellin’ they daughter. I don’t know if you’d consider it 

prostitution. She a dopehead, so she let somebody fuck her 9 year old daughter cause she 

wants dope” (Interview 129). 

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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.
65

● An Individual Hustler: “I work on my own, gangs get into too much trouble. Can’t trust 

nobody but yourself.”

However, we restricted our analysis to gang involved facilitators given that this was the explicit 

focus of our research. 

III.B.1. Race and Ethnicity

Our findings run counter to the local perception that ‘pimping’ is primarily associated 

with African American street gangs. We found that gang-involved facilitators were tied between 

White (n=11), Black (n=11), and Hispanic (n=11). The total number of facilitators (whether gang 

involved or not) was White (16), Black (15), and Hispanic (11). Our data set also included 

Filipino (1), Native American (1) and Vietnamese (1) facilitators. We believe Asian Americans 

are under-represented in our dataset, as are refugee communities previously identified as being 

involved in trafficking (including Chaldean Iraqis, Somalis, and Ethiopians). 

African Americans are over-represented in the California prison system where the 

majority of our interviews took place. African Americans make up just 6% of California’s 

population, but 26% of the incarcerated population (US Census, 2010). White Americans are 

under-represented in prison system, making up 40% of California’s population, but 26% of the 

prison population. This leads us to believe that the ratio of White to Black facilitators may be 

much greater than is represented by our data, and certainly greater than the public consciousness 

imagines. 

White facilitators largely belong to Skinhead gangs (Aryan Nation, Hells Angels) and 

most often mentioned setting up shop within massage parlors, escort services, and strip clubs. 

Mexican American gangs do not openly admit to condoning, supporting or engaging in 

pimping/prostitution, but many are involved in it (individually and as a group). Discussed in 

more detail below, Hispanic facilitators frame their involvement as “protectors”, “guardians”, or 

“managers”. The exceptions are large, organized street gangs – the two largest being MS-13 and 

Logan Heights. When ‘pimping’ occurs in this way – as a formal gang activity – taxes are 

typically paid to higher-ranking associates in the group (e.g., one-third to two-thirds of profit

goes to those above them; typically some of that goes to Mexican Mafia prison gang).

Black gang members were more likely than Mexican gang members to identify pimping 

as one of their group’s top 3 money making activities (often number 1 or 2). Other activities 

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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.
66

included: drug sales, robbery, burglary, and gun sales. Mexican groups’ top illicit activities 

varied but typically included drug sales, car theft, border smuggling (of drugs people and guns), 

and enforcement for Mexican cartels. Pimping typically ranked lower than the other crimes.

III.B.2. Typology of Facilitator Roles

A working typology of facilitators emerged from our analysis of interview data. We 

identified 4 main archetypes with associated characteristics and preferred strategies: Traditional, 

Vicious-Violent, Enforcer/Contractor, and Organized Crime Rings. 

Traditional facilitators are the most likely to use the term ‘pimp’ to describe themselves, 

and to take pride in this identity. The traditional facilitator’s identity as a pimp is tied to the 

desire for social recognition and status. Sometimes described as ‘flashy’ pimps, by other 

traditional facilitators were more likely to show their wealth through material items. As if to 

prove the point, a recent operation that rescued 60 victims from San Diego’s BMS gang (a 

network of “Black MOB” and “Skanless” gangs, along with Neighborhood Crips, Lincoln Park, 

and West Coast Crips) also seized “six luxury cars; flat screen televisions; several thousand 

dollars in cash; numerous pimp paraphernalia such as cups, sticks, and hats; and more than 50 

pairs of Air Jordan shoes.

Traditional pimps manage between 1-10 individuals on average. Their preferred methods 

of coercion (according to their own self-reporting) are Economic and Psychological. With regard 

to the former, they keep all, or the vast majority, of money made in each sexual encounter. 

Everything. You’re supposed to give everything to him. The thing is to 

decipher if he’s going to splurge on the girl or keep the money. They have 

their own debate between pimps about how money is used. A prostitute 

may have to do above the call of duty to keep her maintenance up (i.e. 

getting hair and nails done), while other pimps will pay for their 

maintenance as part of the deal (Interview 098.34).

A pimp is a guy who collects all the funds from a female, he doesn’t give her a 

cut. The only thing she gets is materialistic things and the fact that she’s with a 

pimp, a lot of girl prostitute to make the guy happy. And then, some pimps, they 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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67

take care of the girls, you know, give em a place to live, buy em expensive things 

and gifts, but pimps does not gives girls cuts, they keep it all, they dictate the 

money (Interview 98374.3). 

Traditional pimps feel a sense of ownership over women; for example referring to them as ‘my 

girls’. However they vary along a continuum of ‘niceness’ or lenience, which includes levels of 

control over girls and women’s activities, and whether or not they are violent. Traditional pimps 

also have no qualms admitting that they work with minors.

A subcategory of Traditional facilitators, are Vicious-Violent facilitators, individuals who 

use the greatest coercive force with CSEP and CSEC. The vernacular for this category is “gorilla 

pimp”. The term does not denote racial background, but rather people who use extreme tactics of 

physical and psychological control.30 They control every aspect of commercial sexual 

exploitation, even after they are relatively satisfied that the victim will not try to escape. 

According to a former member of MS-13, getting CSEP to this point – the point “until they 

break” – involves verbal and physical abuse until “finally you realize ‘I better make the best of 

this’. You realize you’re not going anywhere. [It takes] three weeks to break someone, because a 

lot of girls try to run away...”

Once they can be trusted, the pimp's gonna give 'em the man that they’re going to get. 

The pimp's gonna send the john to them. They can’t just go out and get johns on their 

own. If they do, they’re gonna get the shit beat out of them. You see? And the pimp can go 

anytime and check where that dates' being done, what's going on. So he knows, you 

know? (Interview 983.2)

Vicious-Violent facilitators use psychological and physical violence to force high 

financial quotas. They are willing, and perhaps prefer, to recruit minors because of the 

malleability and vulnerability of young people.

 

30 As best as we can make out, the term ‘gorilla’ refers metaphorically to someone who is not intelligent or 

verbose enough to use persuasion, the promise of love and romance, or provision of emotional security as methods 

of control. The two gorilla pimps in our sample used reported using exactly the same combination of coercive tactics 

(Physical, Economic and Psychological Coercion).

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68

Of a prostitute, I’ve seen someone as young as 9 years old.....[At the] Chester Inn - the 

people that lived above us – he pimped out girls all the time, and you’d hear ‘em getting 

banged on the floor and beat up, her crying... and I’m like, ‘Oh my gosh..’ And the sad 

thing about it is the manager let drugs and the prostitution go on there. And she’s still 

there. I’m like, ‘That’s absolutely crazy. Cuz everybody gets away with it there. And it’s 

so dangerous, I mean, people could almost get killed, how bad they get hurt, you know, 

by these pimps (Interview 23.54).

Over here, that I’ve seen personally, I’ve seen junior high school girls out there on the 

streets. Forced into the trade. Held hostage in San Diego. [The pimp] was a Samoan guy 

(Interview 76.345).

Descriptions of Vicious-Violent facilitators (as in the two accounts above) featured 

largely in our dataset, even though only 3 out of 153 interviewees self-identified as “gorilla 

pimps”. In the narrative below, one of these individuals describes his strategies of control.

Girls are very vulnerable and they’re very weak minded. You can really 

crash somebody’s dreams down and you can do it to a girl very quick and 

very fast. You know, in the pimping game, you never compliment your ho. 

You don’t want her to think too fine of herself. You know you wanna tell 

her shit like, ‘go clean your fucking face’ when nothing’s on her face. You 

know what I’m saying? You want her to make her feel like she has to 

prove herself to you. You don’t want that to ever stop. Because once she 

feel like she proved herself to you, she doesn't respect you anymore. Now 

she’s moving to the next pimp (Interview 098.345).

This speaker has a highly objectified view of women. Ownership and possession are 

central to the commentary above. The speaker understands that even a person in his clutches has 

agency (the agency to move to the next pimp), but believes that ultimately he can control that 

agency through psychological and physical coercion. This is why the defeat of self-worth and 

value is a key strategy. This is textbook psychopathology, and many pimps use a range of 

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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.
69

coercive techniques to recruit and then keep victims “in the game”. However (as stated above) 

many other interviewees described gorilla pimping without admitting to being one, and 

sometimes to argue vociferously against their practices.

Gorilla pimping – I would say is a pimp who will use violence and check 

his hoes when anything happens, if anything goes wrong, he’ll get violent 

with his hoes, punishes them, that’s what he does – no nonsense, don’t 

tolerate nothing, what they say. Yeah, they’re common. They’ll mess 

around and get violent because they feel like they’ll lose prostitutes if they 

don’t. You got guys who will die and kill for their money, even kill 

prostitutes (Interview 42.99)

It is worth contrasting this narrative with a different narrative common to the next 

category of facilitators: the Enforcer-Contractor.

The best pimps are the ones you don’t even know exist. Girl feels comfort 

in that. Most times, the girls don’t need the guys, the guy’s just her 

comfort zone, to feel loved, to feel like you’re her dad, you’re their 

bodyguard; however they feel, you know you’re the protector that knows 

what’s going on...If the money keeps rolling, everything’s smooth, nobody 

gets hurt. People are happy both ways. The girl’s happy, the guy’s 

obviously happy, and the metaphor pimp is happy. So he can continue 

business to make money other ways as well (Interview 987.73).

The speaker above, like all facilitators in this category, rejected the label ‘pimp’ (which is 

why he uses the term ‘metaphorical pimp’ – this was as close as he would come to associating 

his “business arrangements” with those used by “real pimps”.) According to the 

Security/Contractor narrative, women (always described as over 18) prostitute themselves for 

money, and contract men to drive them to specific locations and provide security against rape or 

violence. Facilitators in this category say that they do not impose quotas. They often describe 

being approached or recruited by women. The interviewees describe it as a 'business partnership'.

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70

They approached me and asked me if I knew the area and if I could help 

them out in their business. I would help them find business in El Cajon 

City (Interview 346.90).

You know I have a friend, she rolls with me a lot, most of the time these 

girls don’t even have cars, you just drive them to the hotel to at make sure 

they feel safe, that somebody’s there for them if something goes wrong. 

That’s pretty much how it’s done, I’ve done it multiple times (Interview 

7886.7).

The revenue is split, making this one of the main differences between EnforcerContractor and Traditional pimps. Some facilitators described this as the reason that they held 

other jobs. They speak about their income in line with providing security services, and reject the 

term ‘pimp’ altogether – especially when drawing distinctions between themselves and more 

coercive facilitators. Still, our Social Possessiveness Coercion Scale counted revenue splitting (if 

the cut was 30% or above) as Economic Coercion, and thus 16 of the 30 facilitators in the SPC 

analysis were coded in this way.

Unlike traditional facilitators, Enforcers-Contractors were more likely to communicate 

some level of respect or emotional connections with women. They often differentiated 

themselves from facilitators who used coercive violence. They also tended to have rules against 

having sex with the women they worked with. All 6 of the facilitators from the SPC analysis who 

we coded as using no coerciveness whatsoever, fell into the Enforcer-Contractor category and 

none of the 30 were coded as using sexual or physical coercion. 92% of Hispanics belong to the 

Enforcer-Contractor category, however they make up only 32% of the entire population who 

describe themselves this way. 22% are Black, and 52% are White (including Skinhead gangs and 

a homeless clique). 

Finally, we found credible evidence for a variety of organized criminal rings (OCRs) 

operating in San Diego and the US-Mexico border region. The main difference between gangs 

and OCRs is the latter’s hidden or ‘underground’ nature, and how they are structured. Organized 

crime groups were often described as rings or circles, closed groups where members are 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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71

concerned with secrecy. Very few of the people we spoke to admitted to being involved at this 

level, but many were friends with, or had direct knowledge of, people who were. 

They’ve started forming pimp cliques. I can’t remember all of ‘em but San 

Diego has became like a town of everybody wanting to be pimps and they 

start these pimp committees, cliques and you couldn’t be a part of that 

clique unless you was considered to be a pimp (Interview 348.43).

Now, underground little circles are more powerful than these gangs that 

are trying to make themselves look good, you know the unspoken circles. 

There’s a lot of those in this town. Some people will call them cults, some 

call them organizations organized crime, but there’s a lot of them going 

around (Interview 88.9983).

One such ring was reported to include black gang members, Iranians, Pakistanis, Iraqi, 

Saudi, Russian, and Somali facilitators. Their clientele was high end, and they traded in both 

adults and minors. Other studies have called groups like this ‘hybrid gangs’ (Dank et al, 2014). 

This is a bunch of pimps that all recognize that they are being pimps. It’s 

organized and not organized at the same... infrastructure like a gang. 

Some guys are definitely gang bangers. Saudis mostly, one is Iranian and 

one is Pakistani. Mostly Saudi. Chaldeans too. The Ethiopians pimp out 

Somalis... Russians are more organized. Small community. Mexicans 

kidnap a lot. Especially in Tijuana. I know for a fact they will kidnap, and 

start training kids in their early teens. Boy or girl. Here some too, but big 

time in Mexico.

Interviewer: What about Chinese, Filipino?

Yes, the Asian girls... big money. Especially from across the border

(Interview 7983.3).

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72

Another OCR described during our interviews was a child prostitution ring run by Pacific 

Islanders.

I knew about a prostitution ring that was run out of Pacific Beach, run by 

couple of Islander guys; they would get these younger girls, whipped on 

them, make them do whatever they didn’t want to do. Take girls with 

issues with drug problems and offer them love and support and care, 

really all they’re doing is making a whole bunch of money and this guy 

had 10, 12 girls...They have lists and they hold onto those lists. There’s 

prostitution rings with the same johns, co-workers maybe that you have 

that you don’t even know about, that are on these lists (Interview 

9834.22).

Other groups included a devil worshiping group that “give young girls dope and turn 

them out, take them to hotels and put them to work” (Interview 17.33), and a closed Sureno ring 

operating in a nearby reservation and linked to the tribe’s casino (Interview 38.876).

The Native Americans are making their money from the casinos, so they’re 

hiring...okay, say I live on the res, my friend’s coming out and he’s a pimp 

- he’s coming out and I’m gonna take half of his cut for giving him my 

casino. Because the native [American] is going to work it first. But then, 

somebody wants to step into that territory because they know that’s where 

the money’s at. So then they start dealing with the Native Americans... 

(Interview 00.55876).

Several individuals told us about smuggling children and women to and from Mexico.

I do know there is a slave trade going on, where girls are taken from here 

to Mexico, kidnapping is what you call it...I have considered part of the 

slave trade, taking women to go down there (Interview 040.33).

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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.
73

The Mexican people that come from, say, way down South, Oaxaca, or 

Michoacán... They'll tell the family, let us bring your 10 year old daughter 

over here, we'll put her to school, you know, and then they get her over 

here and they're working the restaurants and on the weekend they're 

pimping her out, and she's having sex with the husband in the house, and 

so... it's um, the majority I've heard about it has been family members 

themselves (Interview 50876).

As a specific example of the latter, an MS-13 clique in San Diego operates as a closed group. 

The speaker below, responsible for trafficking girls from Mexico, told us how it worked in her 

experience.

[MS-13] get girls from Mexico, lot of illegals, obviously. Sometimes 

they’ll get work passports, but usually fake passports used to come across. 

They don’t have to pay if they come with us, because they have to work [as 

prostitutes]. That’s their way to get to the States. A lot of the girls cry a lot 

when they get here first...Ages – anywhere from 15-22, they’re younger. 

Youngest I met was 14 (Interview 5.9882).

Another respondent told us that 18th Street gang in Tijuana also organizes sex trafficking. 

This individual was from a Hispanic street gang in San Ysidro, a town adjacent to the USMexico border, who had ties with the Arellano Felix cartel. He told us,

They got prostitutes coming from Mexico, and have even Russians coming 

across the border, they’re Russian. White girls who can’t speak a word of 

English. They stash them in a clavadero (safe house). I see Chinese, too. I 

know they’re going to LA or Vegas. They call from LA, “Hey, we got 3 of 

them.” Each one was going for $10,000. They were pretty girls, I think 

they were Russian, because they couldn’t speak English or Spanish. Like 

18-19 years old. And they got kids, too. Boys too. Homosexuals coming 

over here and buying them for $50,000-$60,000. 17-18 years old little 

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74

kids, and they have those fucking predators coming over to buy them. Sick 

motherfuckers....The prostitution is run by 18th St. in TJ (Interview 

8098.8).

Another organized crime group is a Chaldean Iraqi organized crime syndicate, 

headquartered in Detroit, and with ties to the Sinaloa cartel and the Mexican Mafia. “Chaldeans 

pimp a lot, mostly white, some of their own. They don’t like black girls” (Interview 798.7).

Subsequent field research in El Cajon, where the majority of Iraqi refugees are housed when they 

arrive in San Diego, indicates that sex trafficking of Iraqi youth continues to be a problem. 

Other rings included a “big circle that pimps gays”, a brothel in North Park, a residential 

brothel trafficking children from the Philippines, and an elite “black book” ring that trades in 

adults and minors.

III.B.2 Organization

There exist many types of relationships between individual facilitators and their gangs. 

These range from individual/s doing it on the side (with no involvement from – or profit to –

their gang), small cliques of members (in some cases collaborating with other groups or 

individuals outside of gang), to significant proportion of members involved with the group (or at 

least group leaders) profiting. In some cases, individuals not involved in gangs reported that they 

have working relationships with gangs or gang members.

The majority of research on street gangs has revealed them to be largely informal and 

disorganized groups whose criminal behavior is generally opportunistic in nature (vs. specialized 

to a particular type of crime) (Klein, 1995) and whose primary criminal activities involve 

retaliatory violence against enemy groups and recreational drug use (Decker and Van Winkle, 

1996; Klein, 1995). And while many gangs have members engaging in drug sales, for the most 

part this is not an activity through which the entire group profits and/or is organized around 

(Maxson and Matsuda, 2012).

Although there are exceptions to these findings of gangs being generally loosely 

structured and lacking cohesion or strong organization (Venkatesh, 1996; Taylor 1989; SanchezJankowski, 1991), and debates about what is a gang versus a drug crew versus an organized 

crime group continue to play out in the literature (Curry and Decker 1998; Esbensen, 1993), 

much of the research of the past sixty years has supported this central premise (Klein and 

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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.
75

Maxson, 2006). Street gangs are generally not cohesive, informally structured groups that engage 

in opportunistic, unspecialized or “cafeteria style” criminal behavior (Klein, 1995). Their 

primary form of criminality is retaliatory violence (Decker and Van Winkle, 1996; Kennedy, 

2012). 

Given the limited state of the field on this question, we contrasted directed with 

undirected sex trafficking, the former defined as individual activities dictated by, and directly 

profiting, a gang and latter oppositely defined as individual activities not dictated by, and 

directly profiting, a gang. In our preliminary analysis, we found that pimping in San Diego 

County was almost evenly split between directed and undirected facilitation: Out of 72 gang 

members (34 of whom were facilitators, and 38 of whom did not identify as facilitators but who 

had knowledge of how ‘pimping’ worked in their gang) 25 reported that ‘pimping’ was purely 

entrepreneurial (undirected), 29 reported that it was an operation taxed and/or organized by their 

gang, and 14 facilitators reported arrangements and understandings that represented both directed 

and undirected facilitation.31 For example, one person described pimping as something that he 

and his clique did, but said it was “not a 'whole gang' thing” (Interview 872.11). Another told us 

that “pimping don’t get taxed, just drugs” (Interview 98726.3). Other facilitators told us that their 

personal motivation was purely entrepreneurial, even though (in some cases) they had to pay 

taxes up the chain (thus the gang profited, but did not dictate). 

It’s not an ‘oh, I sell drugs and I’m giving it to the gang, we put it in the hat. I’m 

pimping for the gang.’ Everybody does their individual thing and how it profits 

the neighborhood is how it profits the neighborhood. So if I’m a pimp and I’m 

making money off of prostitutes, you sell drugs, I go buy drugs from you, that’s 

how it go. That’s how a lot of the money is generated. It’s not so much like this 

whole mafia Al Capone Scarface type thing like it’s portrayed, you know, I mean.

We took a closer look at the relationship of gang organizational complexity to directed 

sex trafficking. The full analysis is reported in Appendix C but in sum, we found that directed 

trafficking is positively and significantly associated with gangs that have clear rules of conduct, 

and a promotion structure. We also found that gang members’ use of violence is positively and 

 

31 An additional 4 interviews were coded ‘inconclusive’ on this question.

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76

significantly associated with organizational complexity (specifically territoriality, duration, role 

differentiation, promotion, and tax structure). 

These associations cannot be taken for causal relationships however. In fact, causality 

may even run the other way.32 That is, being involved in directed sex facilitation might induce an 

organizational change toward greater institutional rule generation and the possibility for 

promotion. Gangs that rely on street-level facilitators to “kick up” a percentage of revenues to 

face an information problem: they do not know what the total amount earned by each facilitator 

is. Therefore, they may choose to institute norms and rules that guard against the possibility of 

fraud, as well as incentive structures that promise future rewards for present loyalty.

III.B.3 Coerciveness

We measured the levels of Social Possessiveness Coercion (SPC), defined as a composite 

of 5 grades of force designed to induce compliance and intimidation: Psychological Coercion, 

Physical Coercion, Sexual Coercion, Chemical Coercion, and Economic Coercion.

Psychological Coercion refers to (1) Social and emotional isolation (2) Induced 

emotional exhaustion (3) Monopolization of perceptions (4) Reinterpretation of reality (5) 

Degradation, including humiliation, denial of the victim's power, and name-calling and (6) the 

intermittent reward schedule, referring to occasional indulgences that keep hope alive that the 

abuse will cease. Examples include “Selling a dream”; using love as a tool to manipulate; using 

derogatory terms for sex work; handing money to pimp faces up; walking behind pimp; and 

threats of ‘exposing’ sexual deviance to friends/family (i.e., ‘slut shaming’).33

Sexual Coercion refers to reported instances of rape, or sex acts with CSEP (either 

voluntary or involuntary). Chemical Coercion refers to bringing about altered states of 

consciousness either by providing drugs, or forcing drugs. We did not draw a distinction between 

the two. Physical Coercion refers to any reference to physical violence (such as beatings, slaps, 

punches). Finally Economic Coercion was defined by a high percentage of earnings (about 30% 

 

32 Cases in which causality may be bidirectional or common variation is attributable to a third, latent 

variable are endogenous and should be treated specially, for instance with simultaneous equations which include an 

instrumental variable that is both exogenous and relevant. Here, we have no such IV, as the data collected have not 

been subject to a randomized control trial of some intervention, nor experienced a natural experiment.

33 Our definition of psychological coercion is adapted from BIDERMAN'S CHART OF COERCION. 

Amnesty International, Report on Torture (New York: Farra, Strauss, and Giroux), 1973. The additional four grades 

of force were defined by Ami C. Carpenter.

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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.
77

or above) taken by facilitator. The three most common types of SPC are Economic, 

Psychological and Chemical. Economic Coercion was the most commonly reported type, used 

alone and/or in combination with other grades in by 74% (31) of facilitators. Psychological 

Coercion was reported by 57% (24), and Chemical Coercion was reported by 42% (18). 

Physical and Sexual Coercion was reportedly used by 12% of facilitators. Despite the 

high veracity of their accounts indicated by the list experiment results, we believed facilitators 

might have an incentive to water down their self-reported use of violence. We therefore looked at 

the Survivor Services Dataset for the percentage of victims reported experiencing physical or 

sexual violence: between 14%-30% of victim/survivors report experiencing violence at the hands 

of their pimp or trafficker. 

III.B.5 Online Presence

Canadian cyber-research firm SecDev was subcontracted to conduct social media 

research on gang activity, in order to document the nature of cross-border activity between San 

Diego gangs and Mexican armed groups. The study documented a significant empirical 

difference between the use of social media by African American versus Latino gangs. They 

documented “considerable evidence in the public domain of San Diego-based gangs - especially 

African American and so-called hybrid groups - having used specific social media tools such as 

Twitter to recruit and pimp out women and girls”. However, following the highly publicized 

arrests in December 2014 of the San Diego based Tycoons hybrid gang, specifically due to their 

bragging in social media about pimping and their involvement in prostitution, Sec Dev’s research 

team did not detect any other African American gangs bragging about pimping and prostitution 

in social media. The Tycoon’s case may have highlighted the related dangers to discussing this 

type of behavior and related activities on social media. 

SecDev reported that social media based activity around sex trafficking it is not evident 

in the profiles of specific Latino cartel, gang or affiliate groups on in San Diego. 

Despite being widely advertised online, there was virtually no evidence of Latino gang 

involvement in prostitution and sex work on Twitter. Additional examination of non-Hispanic 

gangs in San Diego and other parts of the U.S. revealed extensive communications between 

affiliates in San Diego and other key prostitution circuit cities, including Atlanta, Phoenix, 

Houston, and others, but no direct involvement in the sex industry. “It is possible, then, that 

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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.
78

gangs are simply not actively discussing their involvement or organizing operational activities 

associated with sex trafficking on Twitter” (Way and Muggah, 2015). Discussed earlier, 

Hispanic gangs are heavily involved in commercial sexual activity, but we found that they do not 

publicly promote or discuss their activities on social media. 

III.B.6 Transnational Connections

The social media mapping study also found a high level of exposure of several Latino 

cartel and gang-affiliated members in San Diego, Tijuana and more widely in Latin America. 

Specifically, the research identified 22 San Diego-based gang affiliates using Twitter, many of 

them Surenos. The study found that Latino cartel and gang members are using Twitter to 

communicate with transnational networks. Mexican-based members used Twitter to 

communicate with affiliates elsewhere in Mexico, the U.S., Central and South America.

Likewise, there are examples of specific cartel and gang members with digital 

connections to street gangs in the U.S. as well as cartels in Colombia. On both sides of the U.S. 

and Mexican border, cartels and gangs are using Twitter and other social media platforms to 

coordinate and conduct criminal activities. There are several examples of how groups are 

collaborating online. For example, the armed wing of the Sinaloa cartel, La Gente Nueva, 

routinely used Twitter to coordinate with Los 12s, another subgroup of the cartel. In their 

interactions, confirmation codes, status updates, meeting locations, and individual identities are 

issued, often in code. What is more, content analysis of specific profiles allowed for the 

identification of key leaders, members, and supporters. 

III.B.7 Location of CSA/CSE

We used the location of arrests on penal codes 647b and pimping/pandering etc, to locate 

the most common addresses; in 2013 for example, the majority of arrests took place in 13 

locations, and 10 of these were hotels. To make sure we controlled for the possibility that hotels 

were the most common target for sting operations by law enforcement (as opposed to actually 

being the most common site of CSA), we asked trafficking facilitators this question in our indepth interviews. Facilitators reported that hotels/motels are the most common site of CSA, in 

addition to casinos, and residential brothels. This pattern of activity is associated with concerted 

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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.
79

efforts by San Diego Police Department that targeted El Cajon Blvd in 2011, and the desire by 

facilitators to avoid law enforcement by "staying off the street".

III.C. VICTIMS

While the weight of our research for this project centered on the scope and nature of the 

facilitation of sex trafficking, we were able to gather data on 869 victims from 8 social service 

agencies (167) and one diversion program for those arrested for prostitution (702). The 8 social 

service agencies represent 80% of the agencies in San Diego whose intake procedures and 

programming are specifically tailored to sex and labor trafficking survivors. The data obtained 

from these agencies (SSP8 Data) are on survivors in their care between June 2013 and June 2015 

and thus represent active cases. Data from the diversion program (FFE Data) represents data 

collected from survivors for an 11 year period, 2005-2015 (inclusive). Because of the careful 

record keeping of the director of Freedom from Exploitation, the diversion program, we were 

able to distinguish between who were sex trafficking survivors and who would not qualify as sex 

trafficking victims by the standards of this study. Each of these sources of data on victims 

allowed us to develop a robust profile of victimization in San Diego County.

III.C.1. Profile of San Diego Victims 

Eight survivor services programs encountered 207 individuals from June 1, 2013 to June 

30, 2015. Of these 207 cases, 167 are confirmed34 unduplicated cases of human trafficking. 

Another source of data on victims of sex trafficking were the surveys administered by Kathi 

Hardy during the diversion program she runs in partnership with the San Diego City Attorney’s 

office. With adults, Hardy’s survey asked about a number of things, including whether 

individuals reported ‘Having Sex to Avoid Beatings’ and/or ‘Having Sex Because of Violent 

Pimp or Partner’, both of which we treated as a proxy variable for force, fraud and coercion. Of 

the 702 people that have been through the program since 2005, 43% qualified as sex trafficked 

individuals – either by force, fraud, coercion, or the fact that they were underage at the time they 

entered “the life”.

Table 6. Distribution of Human Trafficking Cases

 

34 “Confirmed” cases matched the project’s definition of human trafficking victim.

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80

TRAFFICKING TYPE N=167

Sex Trafficking 128 (76.6)

Labor Trafficking 27 (16.2)

Sex and Labor Trafficking 12 (7.2)

However as previously discussed in Section III.B.3 above, the primary methods of 

coercion used by trafficking facilitators are economic and psychological. Hardy’s survey did not 

include items that permitted us to assess levels of either, but the TVIT did. Discussed previously 

in the methods section, we had piloted the TVIT tool so that we could gather evidence of a 

person’s trafficking status using an instrument vetted across multiple agencies. Kathi Hardy 

piloted the TVIT after this study started, and used it in addition to her own survey instrument 

with 81 individuals that came through her program during the grant period. A full 50% of those 

individuals reported evidence of physical, economic and psychological coercion by their 

affirmative answers to the FFE survey items (‘Having Sex to Avoid Beatings’, and/or ‘Having 

Sex Because of Violent Pimp or Partner’), being underage at time of entry into ‘the life’, or their 

affirmative answers to seven TVIT items listed with Table 8. 

Kathi Hardy has also encountered 333 minors since 2003, 321 of whom she has 

classified as CSEC survivors (referred to her as a result of prostitution-related arrests). This 

represents 26.75 child victims of sex trafficking per annum to be added to the adult numbers 

below. As the minors and their guardians in this sample have not given permission for details to 

be shared, and the permissions for our project only include collecting survey data from adults, no 

further analysis can be done on this data at this time. Still, we wanted to include the macro data 

to more accurately reflect the scope of victimization including minors identified by the system. 

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81

Table 7: Percentage of FFE Participants Meeting Legal Definition of Past or Current Trafficking

Adults

% of Total HT designation Total n=702

25% Under age at entry 175

2% Those that identified HT 12

12% Sex because of a violent pimp/partner, i.e. force 86

2% Had sex to avoid a beating, i.e. coercion/force 16

2% Had sex for a partner’s drugs, i.e. coercion 13

43% Total Adult HT Survivors Sept ’05- Apr ’15 302 (31 p.a)

Total Adult HT Survivors Apr ’13 - Apr ‘15 78 (39 p.a.)

Minors

Total CSEC Survivors 2003-2015 321 (26.75 p.a.)

Combined Adults and Minors

Total CSEP Survivors from FFE Data ‘03-‘15 621 (52 p.a.)

Table 8 TVIT data key 

 5c. Have you felt you could not leave the place where you worked or lived? 

 5e. Did anyone at the place where you lived or worked not allow you to contact 

your family, friends or others? 

 5f. Did anyone take and keep your identification – your passport or drivers 

license? 

 5h. Did anyone you worked for or lived with tell you to lie about your age? 

 5j. Did you ever see anyone else at the place where you lived or worked harmed, 

or threatened with harm? 

 5l. Did anyone ever pressure you to touch another person or have unwanted 

physical (or sexual) contact with another person? 

 5o. Did anyone you worked for or lived with ever take your money for 

transportation, food or rent? 

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82

Table 8: 40 trafficked victims out of 80 total cases of FFE and TVIT data combined 

Underage Beating Violent 

Pimp

Drugs 5c 5e 5f 5j 5l 5o

1 x x x x x x x x x X

2 x x x x x x x X

3 x x x x x x X

4 x x x x x x x X

5 x x

6 x x

7 x x x X

8 x x X

9 x x

10 x

11 x

12 x

13 x x

14 x

15 x X

16 x x

17 x x x

18 x

19 x X

20 x

21 x x

22 x

23 x x x x x x x x X

24 x x x x x x X

25 x x

26 x x

27 x x x X

28 x x x X

29 x x x X

30 x

31 x x x x x X

32 x

33 x

34 x x x X

35 x x

36 x

37 x

38 X

39 x x x X

40 x x

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83

III.C.2. Estimating the Scope of Sex Trafficking 

We used three methods to estimate the scope of sex trafficking in San Diego County. 

Each method produces an imperfect estimate, all of which we present here in order to explicitly 

suggest enhancements to data collection and analysis for our region and others who wish to 

duplicate this methodology. From our analysis, the estimated number of affiliated CSEP is 

between 3,417 and 8,108 per year. The first and second method relied on arrest and interview 

data with sex trafficking facilitators, while the third relied on arrest records of individuals 

charged with Prostitution, Solicitation, and Loitering with Intent. 

The first method produces the highest estimate. It relies on a list experiment that was 

conducted during inmate interviews. Participants were randomly assigned to “control” and 

“treatment” groups to determine the administration of two list experiment questions. All 

participants were given two sets of activities that they might have performed, and asked to list 

the number of acts that they had performed in each set. Control group participants were given 

four less sensitive activities (e.g. having more than one sibling; having driven a car over the 

speed limit; having a shoe size greater than 9). Treatment group participants were given the same 

set of four, less sensitive activities, in addition to one sensitive one: having been paid money by a 

sex worker (first question), and having sex with a sex worker (second question). The basic idea 

was that participants will have no inhibitions admitting to an act if it is grouped inseparably with 

a number of other, innocuous acts, though they might not openly admit to the act if asked 

outright. The phrasing of the first question was very intentional: it was developed specifically to 

be non-threatening as opposed to alternative framings such as “Have you ever pimped anyone 

out before?”

Econometrically the list experiment is simple: the outcome number of acts for each of the 

two questions is regressed on the treatment variable. We ran OLS regressions for all participants, 

in addition to regressions stratified by sex of participant. For the first question – whether the 

participant had ever been paid by a sex worker before –a statistically significant 61.7% (95% CI: 

20.7% - 102.0%) of male participants reported that they had been paid by a sex worker. At the 

time of the study, there were approximately 4,150 male prisoners in the custody of the San Diego 

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84

Sheriff’s Department. Assuming generalization to the wider prison population35, the foregoing 

results imply that around 2,561 of them have acted as a facilitator of the illicit sex trade. 

Moreover, according to interview data, the average number of girls per facilitator (in 

response to the inquiry “How many girls does the average pimp work with?”) was between 

4.58

36 as reported by male facilitator, and 8.1 as reported by female facilitators and prostitutes 

interviewed at Las Colinas.37 We might therefore estimate that 2,560 facilitators actually 

represent some total population of CSEP. Combining these two pieces of information – the 

percentage of male participants who reported that they had been paid by a sex worker, and the 

average number of girls per facilitator – we arrive at a range of 11,724 – 20,736 potential CSEP.

The calculation is below, where (TIP) = total inmate population, (stf) = sex trafficking facilitator 

and (afp) = average number of ‘prostitutes’ per facilitator).

4150 (TIP) X 61.7% = 2560 (stf) X 4.58 (afp) = 11,724 prostituted individuals 

4150 (TIP) X 61.7% 2560 (stf) X 8.1 (afp) = 20,736 prostituted individuals 

In Section III.B, we reported that 33% of the 139 inmates interviewed openly admitted to 

being a sex trafficking facilitator when asked outright. Our list question may have been able to 

detect the 28.7% of respondents who did not openly admit to being a sex trafficking facilitator 

when asked outright, but did admit to receiving money from a prostitute when that inquiry was 

grouped with several other innocuous acts. Alternatively, 28.7% of respondents may have been 

paid by a prostitute at some point in the past, but no longer provided services at the time of their 

incarceration and interview thus would not have self-identified as a facilitator. Either way, it is 

worth repeating the calculation above, but assuming generalization to the wider prison 

population at the reported 33% of inmates who openly admitted to being a sex trafficking 

facilitator when asked outright during interviews. 

 

35 The researchers recognize that this assumption is problematic, in particular because we do not know the 

extent to which PC represents the mainline population of inmates, and because our sample is not randomized. We 

present this method as a broad prevalence estimate, and suggest that it can be refined and enhanced for greater 

precision in the future. 

36 SD = 3.19, skewness = 1.32 

37 Despite the low n, It could be argued that the females respondents are better informed, since a greater 

percentage of those interviewed had direct involvement in the illicit sex-trade industry 

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85

4150 (TIP) X 33% = 1369 (stf) X 4.58 (afp) = 6,272 prostituted individuals 

4150 (TIP) X 33% = 1369 (stf) X 8.1 (afp) = 11,088 prostituted individuals 

 

This broad range of 6,272 to 20,736 should be interpreted as a broad prevalence estimate, 

which is a measure of how many people experience a particular crime during their lifetime. It is 

not a measure of incidence – that is, it does not tell us that between 6,288 and 20,736 crimes of 

prostitution took place during a particular period of time. Some inmates with whom we spoke 

had been in prison a short time, others for a long time, and it is unlikely that any of the 

trafficking facilitation reflected by this range was ongoing during our interviews. If these 

numbers are useful, it is in their suggestion that they may represent a number of trafficked 

individuals across decades – depending on the length of incarceration of the individuals with 

whom we spoke (data that we can retrieve, but have not at time of writing). 

The second method starts with counting all arrests of facilitators.38 Unduplicated arrest 

and bookings for 10 Penal Codes (see Table 11 below) generated 2,831 arrests from January 

2007 to June 2014.

PC 236 False Imprisonment makes up the bulk of these arrests, and there are two 

problems with using this particular penal code to count sex trafficking offenders without looking 

at the case files for each arrest. First, it is not possible to know how many labor trafficking cases 

versus sex trafficking cases PC 236 represents. Second, according to the San Diego Police 

Department, PC 236 is applied in a variety of non-human trafficking related cases including 

domestic violence, kidnapping and robbery. A Detective Sergeant at San Diego Human 

Trafficking Task Force with whom we have worked closely for the past 5 years gave us an 

educated estimate that 1⁄4 of PC 236 arrests were linked to sex trafficking cases. Absent the 

ability to access case file data, we opted to use that lower number to perform the calculations 

described below. 

 

38 From Table 3: 236, 236.1A, 266, 267, 266H(A), 266H(B)(1,2), 266I, 266I(B), 266J(A)(2), 266J

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.
86

Table 9: Combined Arrests & Booking for Human Trafficking Predicate Crimes

PENAL CODE OFFENSE ARRESTS

2007-2013

BOOKINGS JANJUNE 2014

236 False Imprisonment 2474 0

236.1A Human Trafficking 103 3

266 Seduce Minor for Prost. 4 1

267 Kidnap Minor for Prost. 4 0

266H (A) Pimping 139 11

266H(B)(1,2) Pimping Minor 14 8

266I Pandering 31 5

266I(B) Pandering Minor 11 0

2661 (A)(2) Pandering by Force 13 7

266J Providing Transport Minor 3 0

TOTALS 2796 35

GRAND TOTAL 2831

Recalculating total arrests with the suggested lower number (25 % of 236 Arrests from 

Jan 2007 - June 2014 = 619) makes for a total of 976 traffickers in the past 6.5 years, averaging 

150.2 traffickers arrested per year. However, those facilitators apprehended by law enforcement 

represent some fraction of the total number of facilitators in operation. It is unknown what that 

fraction is; ideally, one could employ a capture-recapture methodology on sex facilitators to 

estimate the total population. In the absence of a scientific methodology, and based on estimates 

from parallel research on drug and gun trafficking (Goodman & Marizco, 2010; McDougal et al., 

2014), we estimate that law enforcement only arrests 15-20% of the persons committing 

trafficking offenses. We might therefore estimate that 150.2 facilitators apprehended by law 

enforcement each year actually represents a total population of between 751 and 1001 trafficking 

facilitators per year. 

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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.
87

Table 10: Revised Estimates of Arrests of Trafficking Facilitators 

PENAL CODE OFFENSE

ARRES

TS BOOKINGS JAN-JUNE 2014

2007-

2013

236 False Imprisonment 619 0

236.1A Human Trafficking 103 3

266 Seduce Minor for Prostitution 4 1

267 Kidnap Minor for Prostitution 4 0

266H (A) Pimping 139 11

266H(B)(1,2) Pimping Minor 14 8

266I Pandering 31 5

266I(B) Pandering Minor 11 0

2661 (A)(2) Pandering by Force 13 7

266J Providing Transport Minor 3 0

TOTALS 941 35

GRAND TOTAL 976

Recalling average number of girls per facilitator was between 4.58 and 8.1, and assuming 

that law enforcement apprehends 15-20% of the trafficking facilitators operating in San Diego 

County every year, the estimated number of affiliated CSEP is between 3,417 and 8,108 per 

year. The calculation is below, where (tfp) = total population facilitators, and (apf) = average 

number of ‘prostitutes’ per facilitator.

Assuming the lower range of traffickers at 751 per year: 

751 (tfp) x 4.58 (apf) = 3,440 CSEP per year 

751 (tfp) x 8.1 (apf) = 6,083 CSEP per year 

Or, assuming the upper range of traffickers at 1,001 per year: 

1,001 (tfp) x 4.58 (apf) = 4,585 CSEP per year

1,001 (tfp) x 8.1 (apf) = 8,108 CSEP per year 

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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.
88

Truly accurate estimates of victimization deriving from offender arrests requires future 

researchers to gain permission to access case files, both for this reason and because evidence of 

sex trafficking appears to be similarly masked within domestic violence penal codes. A year into 

this study, a Sheriff’s detective brought to us his hunch that (1) a certain number of domestic 

violence incidents were in fact cases of a trafficker violently punishing one of ‘his girls’ and (2) 

that when officers called to the scene believed this to be the case, they recorded those suspicions 

in their field notes. So, we conducted exploratory analysis on all digitized field notes referencing 

domestic violence, from 2008-2013, from the San Diego Sheriff’s Department using the 

following keywords: "call girl" or *whor* or "girlfriend experience" or "hooker" or *pimp* or 

"slut" or "tricks" or "working girl" or "sex worker" or *prostitut* or *pander* or *hustle* or 

"street walker" or *tramp* or *traffick* or "gigolo" or *solicit* or "ho" or "hoe".39

Our initial findings warrant a much deeper look through the individual cases to carefully 

eliminate non-sex trafficking related cases, but our preliminary look at the data leads us to 

suspect that there may be significant undercounting and perhaps under-investigation of sex 

trafficking cases. The Sheriff’s department identified 41,805 unique Domestic Violence cases 

from 2008-2013. This indicates an average of 6967.5 DV cases per annum. There are a total of 

718 unique cases that contain the sex trafficking related keywords in our search. While this 

number represents a small percentage (.02%) of the overall DV arrests, our exploratory analysis 

indicates on average 120 DV cases per year that we would want law enforcement to investigate 

more deeply for evidence of sex trafficking. 

A third method for estimating victimization used arrests for PC 647 Prostitution, PC 647a 

Soliciting, or PC 653.22 Loitering with Intent (CSA) as the starting point. Arrest records from the 

San Diego Police Department and Bookings records from the San Diego Sheriff’s Department 

combined to reveal a total of 5598 unduplicated arrestees between 2007 and 2014 (see Table 8 

below). This means that an annual minimum average of approximately 370 sex trafficking 

victims may have come into contact with law enforcement in San Diego County each year. 

Future analysis can disaggregate the “johns” from those arrested for prostitution for a more 

accurate count. 

 

39 Data Source: RMS. Created By: Laura Curtis and Renae Flores, Crime Analysis Unit

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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.
89

Table 11: Prostitution, Soliciting and Loitering Arrests

PENAL CODE OFFENSE ARRESTS 2007-2013 BOOKINGS JAN-JUNE 

2014

647 Prostitution 288 0

647a Solicitation 399 0

647b Prostitution 3409 193

653.22 Loitering with Intent 948 8

653.22(A) Loitering with Intent 346 1

TOTALS

GRAND TOTAL 5598

Again, 5598 is not to be taken as an estimate of the total number of sex-trafficking 

victims but the fraction of the greater population that law enforcement apprehends. If we again 

use the 15%-20% range for a tentative population calculation, we arrive at a range of 27,990 - 

37,320 individuals, or 4,306 – 5,741 individuals annually. Leaving aside for a moment the small 

percentage in this dataset that represents the proportion of “johns” arrested and/or charged under 

the same penal code (647b), we then asked whether it could be possible to estimate how many of 

these arrests represent individuals who have been induced into CSA through force, fraud or 

coercion? 

Recalling that 50% of the first time offenders that passed through Kathi Hardy’s Freedom 

From Exploitation program qualified as trafficked individuals, we argue that it is plausible to 

expect a similar percentage to operate at minimum within the Law Enforcement dataset. 

Demographics between datasets are almost identical - FFE contains only first time offenders for 

prostitution, whereas the arrests and bookings record repeat offenders. If we then count only 

50% of those 4,306 – 5,741 individuals caught up in Prostitution, Solicitation, and Loitering, we 

estimate between 2,153 - 2870 victims of sex trafficking per year. 

Of the three methods, we believe the second is the most robust because (1) it integrates 

data from two sources - arrest records and in-depth interviews; and (2) this method allows us to 

‘see’ individuals who are not physically represented by an arrest record. As facilitators would put 

it, this method allows us to see ‘the stable’ (the obnoxious term used to refer to the number of 

prostituted individuals a pimp makes money off of). As we put it, this method allows us to ‘see’ 

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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.
90

in the data other individuals working in nearby hotel rooms when one gets busted in a sting; or 

the individuals connected to one particular pimp or trafficking facilitator when he was arrested. 

III.C.3. Gender

The sex trafficking victims that come into contact with San Diego social service agencies 

and that are arrested for prostitution are overwhelmingly female. Of the 140 cases of sex 

trafficking documented by the social service agencies we worked with, 138 (98.6%) were female 

and 2 (1.4%) were male. Of the 250 respondents for which we had gender data in the diversion 

program data, 243 (97.2%) were female, 5 (2%) and 2 (0.8%) identified as LGBT40.

III.C.3 Age

We were able to estimate from the two sources of victims data with great confidence the 

average age victims are at the time of intake, and with some confidence the average age of entry 

into sex trafficking for San Diego victims. The two different sources of data we relied on to build 

a profile of victims in San Diego produced different results on the average age at the time of 

intake. The age at intake for the victims cared for by social service agencies ranged from 13-46 

years. Victims were on average 35 years of age at the time of intake. Table 14 below displays a 

breakdown of age ranges for the 140 survivors in our dataset from the eight social service 

agencies (SSP8 Data).

Table 12: Age at Intake from SSP8 Data

 13 to 17 years 42 (30%)

 18 to 24 years 58 (41.4%)

 25 to 34 years 25 (17.9%)

 35 to 46 years 15 (10.7%)

Data from the Freedom from Exploitation interviews reveals that the average age at the 

time of intake for adults arrested for prostitution was 23.78 years (see Table 5), while the average 

 

40 The percentage of victims who would identify as LGBT may be larger as the director of the diversion 

program had only been collecting data that distinguishes these gender identities in the last three years. 

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.
91

age for minors at the time of intake for the same program was 14.5 years41. We therefore 

calculate the average age at arrest for sex trafficking survivors at:

Average Age at Intake for FFE Sex Trafficking Victims

(302x23.78125) + (321x14.5)/(302+321) = 7181.9375 + 4654.5/623 = 19 years of age

The average age at intake reveals the age at which victims are being referred for services 

and not the age they were forced into sex trafficking. Data from our social service agencies did 

not include sufficient detail to determine the average age of entry for the 140 victims they served 

between 2013 and 2015. However, we are able to estimate the average age of entry into sex 

trafficking from the FFE data.

Data from the adult interviews in the diversion program reveals that the mean age of 

entry into CSA is 17.8 years old, however the mean age at time minors were arrested for 

prostitution in Hardy’s sample is 14.5 years of age (interview with Hardy). We would naturally 

assume that the average age of entry for the minors in the FFE program would be lower than at 

the time of the program, but we have no reliable data on which to base a judgment about just 

how much lower the average age of entry would be. Knowing the average age at the time of 

intake gives us a maximum age to add to the adult arrestee data to make more robust estimate of 

the average age of sex trafficking survivors from our FFE. With these two estimates - the mean 

age of entry for minors with the average age of entry for adults – we estimate an average age of 

entry into sex trafficking in San Diego of 16.1 years of age42. 

Average Age of Entry for San Diego’s Sex Trafficking Victims:

(302x17.8)+(321x14.5)/(302+321)= (5375.6 + 4654.5)/623 = 16.1 years of age

 

41 Calculated by our consultant and FFE program director Kathi Hardy.

42 We suspect this number is lower based on the assumption that CSEC victims in our sample were likely 

younger when they were drawn into trafficking than when they were caught. But given the significant size of the 

sample, we do not expect the number to be dramatically lower. If, for example, the average age of entry for the 

minors in our calculation was 12, we’d calculate the average age of entry at 14.5.

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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.
92

Table 13. Age of Adult Survivors at Time of Arrest vs. Age of Entry

Age at time of FFE program Age at entry into sex trafficking

Mean 23.78 Mean 17.8

Median 21 Median 17

Mode 19 Mode 17

Min 17 Min 1.5

Max 55 Max 53

Count 288 Count 290

III.C.4. Race and Ethnicity of Sex Trafficking Survivors

Of the confirmed survivors in FFE, 28% identify as Black, 25% as White, 25% as 

Mixed/Biracial and 14% as Latino. As the black population of San Diego is only approximately 

5%, black victims are overrepresented more than five times their population. White victims and, 

to a lesser extent, Latina victims are somewhat underrepresented in the population of sex 

trafficking victims. We have a suspicion that the percentage of Asian victims is 

underrepresented given evidence to the contrary in our interviews with facilitators. This 

underrepresentation in our sample is likely due to at least two major factors: 1) a percentage of 

Asian victimization is hidden in the Mixed/Bi-racial category that we cannot disaggregate in our 

dataset and 2) we believe the sample is biased toward black victims given the disproportionate 

representation of black citizens and underrepresentation of Asian citizens in the prostitution 

arrest records. Native Americans are overrepresented, as they make up less than 1.2% of San 

Diego County residents, but approximately 2% of the population in FFE.

Statistical analysis also shows that Native Americans were much more likely (3 1⁄2 times 

more likely) than whites to report having sex because of a violent pimp or partner. 

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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.
93

Figure 2 – Ethno-Racial Profile of FFE Adult Dataset

III.C.5. Geographic Distribution of Victims

The majority of trafficked individuals live in 10 zip codes, displayed below, but survivors 

have been identified county-wide (see Figure 3). This data was consistent with what we learned 

in independent conversations with law enforcement and the data from our school focus groups. 

Each of these zip codes identifies a particular neighborhood or area of the city that is home to one 

or more street gangs: to give just three examples 92113 (Logan Heights) has seven street gangs; 

92114 (Southeast San Diego) has six gangs; and 92102 (Golden Hill; Market Street) is home to 

four gangs with multiple cliques.

Table 14. Zip Codes

Zip 92113 92105 92115 91977 92114 92101 91950 92104 92102 92020

Freq 25 22 18 18 16 13 13 12 11 10

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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.
94

Figure 3 – Countywide Location of Individuals at Time of Arrest 

III.C.6 Country of Origin

Sex trafficking victims in the social service system are primarily born in the United States 

(79.3%). The next most significant country of birth is Mexico (11.4%) with less than 10% of 

victims born in one of the following countries: Cameroon, China, Colombia, Germany, 

Honduras, Kazakhstan, Korea, Philippines, Puerto Rico, Russia, and Taiwan.43

III.C.7 Victimization, Homelessness and the Foster Care System

We found a strong correlation between victimization, homelessness and foster care. In our 

sample of adult survivors of sex trafficking, 55% reported that they were or had been homeless, 

28% reported they had at some point in their life been in the foster care system and 17% reported 

having experienced both homelessness and the foster care system. We could not distinguish 

whether the homelessness happened as teenagers or as adults, but the results of our analysis add to 

 

43 As an aside, we identified 39 cases of labor trafficking from this data. Females accounted for 69% while 

males for 31% of labor trafficking victims. The labor trafficking victims were predominantly from other countries, 

Mexico (30.8%), Philippines (17.9%), Ethiopia (7.7%), Guatemala (5.1%), Indonesia (5.1%), Kenya (5.1%), Russia 

(5.1%), Other (including the US): (23.1%).

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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.
95

the evidence that homelessness and sex trafficking are highly correlated. This confirms previous 

studies, including research by the Covenant House of New York. According to Bigelson (2013: 

6), 

“Shelter was the number one commodity traded in return for sexual 

activity. Of those who engaged in commercial sex activity, almost half –

48% in total - said they did it because they did not have a place to stay. 

Participants explained how traffickers loiter in areas where homeless youth 

are known to gather and then tell them that the shelters are full and offer 

them a place to stay in lieu of sleeping on the streets.” 

In situations of domestic trafficking, adolescents who are runaways, “delinquents,” or labeled as 

“troubled” are more vulnerable to sex trafficking recruitment (Mitchell et al., 2010; Williamson & 

Prior, 2009). 

Our results also raise concern about the coincidence of trafficking and experience in the 

foster care system. Our data on adult survivors of sex trafficking did not include sufficient detail 

to determine if the trafficking experiences happened during or after their time in Foster care. Using 

FFE survey data – specifically, answers to the two prompts “Have you ever been or are you 

currently homeless?” and “Have you ever been in foster care?”, we calculated that those who had 

gone through foster care were 2.63 times (P>|z|=0.000) more likely to be homeless than those who 

had not gone through foster care.

III.C.8. Recruitment by Traffickers and Gangs in San Diego High Schools

The research team worked with San Diego County schools to gather and analyze crime 

incident reports from 20 high schools, making this study one of the first in the United States to 

include schools as a data source for studying sex-trafficking. Focus group members were asked 

to recall incidents from 2010-2015. In total, the high school staff in 20 high schools across the 

county identified 417 reported victims along with an additional 60 suspected victims in the past 5 

years (averaging around 95 victims at least suspected per annum).44

 In terms of primary and 

 

44 Victims Reported refers to individuals identified within last 5 years - self-identified by student, or case 

reported to law enforcement, school admin, or social services. Victims Suspected refers to suspicions based on 

indicators present, but did not reach level of reporting, investigation or action. Gangs refers names of gangs that 

students may affiliate with or associate with on/near campus.

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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.
96

secondary prevention, high school staff has an extremely a high exposure to victims and 

suspected victims of CSEC.

Across 20 school focus groups, school personnel reported a total of 69 distinctly named 

gangs and an additional 15 unnamed gangs. Of these, 31 named and 7 unnamed gangs were seen 

as involved in HT/CSEC activities. When asked what gang activity is like among high school 

students, staff at multiple high schools reported a change in overt gang presence and activity in 

last 5-6 years (reported by SUHSD-05, SDUSD-02, SDUSD-08, SUHSD-02**, SUHSD-06). 

Staff talked about more tagging and “wannabe’s” these days (more discreet). SUHSD-02 staff 

said that gang activity tends to come in waves based on leaders being incarcerated or released. 

SUHSD-12 staff said that changes in overt gang activity may be due to technology - ease of 

social media means recruitment can be covert and off-site

In their own words:

“I don't pretend to be an expert about gangs, or really anything, but what I do 

know, a couple of things, that there are waves. A lot of it is due to which folks are 

being incarcerated and which ones are being released. So like former gang 

members are released and come back in the communities, and they start 

recruiting so that ebbs and flows. So there's that part of it. It’s cyclical. We are 

currently in a down, a lower level kind of activity but it never goes away. The 

proof is in those kinds of things like, the annual community events where everyone 

comes out in their full regalia and all that, so it's there. And the tagging is there. 

I'm sure the classroom teachers see it also in the notebooks and folders. I think 

kids in general have gotten more sophisticated and are probably doing a lot more 

of their stuff online. They're not so open with it because they know in general 

schools have really buttoned down on their policies, on their zero tolerance or 

very low tolerance to that kind of stuff. They've really cracked down and forced 

them under ground. We could debate all day about which is better or what have 

you, but in terms of the school environment it's definitely much better, in terms of 

there's not a lot of overt gang activity. Lately that's how it's been. But we have 

had, this community does have a long history of all kinds of gangs...” (SUHSD02)

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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97

When asked how gangs are involved with recruitment/victimization of students, staff said 

that gangs recruit girls for prostitution by “swooping in” on newcomers and having women 

recruit other women (GUSD-01). A consistent theme throughout multiple focus groups was that 

many youth are also recruited by family members and “implicitly” through generational or 

cultural ties (GUSD-01, SUHSD-02, SDUSD-01, SUHSD-04, SDUSD-02, SDUSD-03, 

SUHSD-05, SDUSD-05, SDUSD-09, SDUSD-10). Some staff mentioned gang-organized 

massage parlors (SDCOE-01). One school saw evidence of a connection between gangs with 

drugs, arms, and human trafficking (SUHSD-01) but could not share in detail. Staff at one 

school felt that some neighborhood gangs have a strong grip on human trafficking in San Diego, 

with human trafficking as one of a couple key gang trades and involving gang members across 

the board (SDUSD-12). Another staff member at the same school mentioned that not everyone 

is likely involved to the same degree-some may associate with the same places and 

neighborhoods, but not be officially “involved”

In their own words:

“Every gang's got their hand in it. It’s a lot easier than dealing drugs these days.” 

(SDCOE-01)

“[The boys] start talking about it at 13. Bragging. We also, we study the topic in class, 

they often will try to defend it. The guys will often say that the girls want to do it, we're 

just helping them. Rather than victimizing...” (SDCOE-01)

“Second thing is, you see them because you see their parents, because you're talking 

about generational gangs. You're not talking about the fact that this kid showed up and 

was converted or brought in. Look at the dad. I mean, you have parents that walk in that 

have the whole tattoo thing. They may be, or may not be, but they look like it. They're 

dressing the way you would dress. That's part of the thing. It's a generational thing, with 

many of our students here. I don't think it's something you can leave. There are kids that I 

remember having conversations with, where the only way they’re going to leave is if they 

leave their family. It is their family. In other words, this is so ingrained generation after 

generation. So would I say there's violence or it's really over? But is it here? Yeah, it's 

here.” (SUHSD-02)

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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98

III.C.9 CSEC Risk Factors

School staff thought of a wide range of factors that led to students being most at risk for 

sex trafficking victimization. Table 16 contains summary data.45 Factors included being lonely, 

isolated, vulnerable, without a hope for the future (GUSD-01), in poverty (GUSD-01, SUHSD02), newcomers to school (GUSD-01), in special education (GUSD-01, SDUSD-03), with 

previous sexual abuse (GUSD-01), with family involvement in “the life” (GUSD-01, SUHSD01), runaways from home, homeless youth (SUHSD-01, SUHSD-02), undocumented persons 

fearing deportation (SUHSD-03), being LGBTQ (SUHSD-02, SDUSD-09), having family 

instability (SUHSD-02), having drug addictions and being refugees or students with cultural 

trauma (SDUSD-07). There was particular concern about the power of female recruiters or 

facilitators operating on school campuses.

In their own words:

“The female recruiters, the female CSEC girls will tell us how they recruit. And they do, 

they look for the girls that are poor, lonely, kind of the isolated, vulnerable students. 

Whether it's male or female, there is kind of a sense of who is low hanging fruit that they 

can go after.” (GUSD-01)

“The biggest theme I've seen on this campus and in the young women I work with is 

sexual abuse. And that is a really huge red flag, because from what I've seen, all the girls 

that have been involved have past sexual abuse sol they're more susceptible to be 

recruited.” (GUSD-01)

“A lot of our kids, even though they are street smart, they’re very naive. Their world is 

very small. And so they’re gullible, they’re easy targets, in general, and then you throw 

in the financial. Most of our kids are definitely way below the poverty level, so anything 

material could entice them. Their parents are often working multiple jobs, so there's the 

 

45 The key to Table 14 is as follows: Confirmed/Suspected = # instances mentioned by staff across all 

focus groups, associated with confirmed/suspected case; Perceived = # instances mentioned by staff across all focus 

groups, not associated with a confirmed/suspected case; and # Schools = # schools that mentioned this factor.

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.
99

absenteeism from the parents. They walk long distances...So there's that easy access to 

target someone in the public transportation system and walking everyday.” (SUHSD-03)

“Because when she ended up in a group home, she ended up meeting another young lady 

who was deep in it and now that’s how she ended up with a pimp. And so, a year later I 

was able to talk to her again. And she basically gave me a lot of the ins and outs on how 

it works. Craigslist is basically the way they go. They honestly don’t see... it’s a different 

world. To them, this is what the world is like. And so, they don't see anything wrong with 

it. ‘It’s the way the world works’ and they see a lot of adults that are in very high 

position, whether they're doctors, or lawyers as clients, so to them, if these are the people 

that are clients, then ‘what’s wrong with it?’” (SUHSD-03):

Table 15: CSEC Risk Factors 

Confirmed/Su

spected

Perceived #Schools

Financial Factors 1

a. Financial problems/need or want money 10 8 9

Education Factors 2

a. Dropped out/Leaving school

b. Special education students/learning difficulty

9

8

4

2

7

7

Newcomer 3 Factors

a. Newcomer/new arrival

b. Refugee

c. Undocumented/new immigrant

d. Crossing border/family members across border

2

3

2

6

1

0

5

3

2

2

5

7

Health/Safety Needs 4

a. Physical or behavioral needs

b. Mental/emotional health needs

c. Sexual or reproductive issues

d. Pregnant or new mother

e. Involvement with drugs/alcohol

8

5

2

10

17

2

12

1

4

9

4

9

2

7

15

Trauma/Violence 5

a. Previous sexual abuse or rape

b. Physical abuse

c. Emotional abuse or neglect

d. Previous trauma or PTSD

e. Victim of kidnapping

f. Violence or high conflict in the home

3

6

1

1

5

3

0

1

3

2

2

0

3

6

2

3

3

2

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100

Parental and Home Factors 6

a. Lack of parental involvement

b. Kinship care

c. Family member or partner incarcerated

d. Adults deported or moved

e. Single parent

f. Permissive or promiscuous parents

g. Family involved with drugs

8

9

4

1

1

5

7

20

1

1

1

1

1

0

14

7

4

2

2

3

3

Transitional Lifestyle 7

a. Runaway, "in and out" of home or "disappearing"

b. Homeless or transient lifestyle

c. Foster care or alternate group home

d. Frequent mention of traveling

24

10

4

3

5

2

0

0

16

7

3

3

Social Factors 8

a. Lonely, isolated

b. Naïveté or lack of healthy social skills

c. Sophisticated and way past age group

d. Low self-esteem

e. Unusual interaction patterns with other students

0

0

0

0

2

5

2

2

4

0

5

2

2

3

2

Dating and Sexuality Factors 9

a. Involved with an older man/boyfriend

b. Same-sex attraction or LGBTQ identity

c. Multiple girls with same boyfriend

d. Online relationships or solicitations

24

2

2

3

9

0

2

4

15

1

3

4

Relationships with Others in “The Life”

a. Family member involved in CSEC/prostitution

b. Family member approving/arranging CSEC 

c. Family involvement with pimp/gang member

d. Women recruiting women into CSEC/prostitution

e. Personal involvement with pimp/gang member

f. Involvement with drug cartels

g. Involvement in a prostitution ring/room

h. Involvement with street prostitution

9

12

4

18

7

1

3

6

0

0

0

6

3

3

0

1

8

9

3

11

9

4

3

4

Socio-cultural Factors

a. CSE or lack of female rights normalized in culture

b. Normalization of older boyfriend

c. Sexual activity normalized in school/social media

3

3

4

7

1

3

6

2

7

III.C.10. Incentives for Recruitment

Staff commented on how students are recruited for commercial sexual exploitation. 

(Table 17 contains summary data.) The methods they talked about included gang recruitment 

(GUSD-01, SUHSD-02, SUHSD-03), with active gang members recruiting new members with 

material enticements (SUHSD-03), “Swooping” in on newcomers to school to recruit into 

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

gang/prostitution (GUSD-01), gang members recruiting at a party (SUHSD-02), gang members 

in vans approaching middle schoolers (SUHSD-03), participation in prostitution ring (SUHSD01, SUHSD-02), involvement with drug cartels (SUHSD-01, SUHSD-06), involvement with an 

older boyfriend (SUHSD-01), parents offering their kids to friends/associates b/c of need of 

money (SUHSD-02, SUHSD-03) and a widespread use of social media, including the circulation 

of child pornography on the internet (reported by SDUSD-10 as across schools).

Table 16: Summary Data on Incentives for Recruitment to CSEC

Confirmed/

Suspected

Perceived #Schools

Material Considerations 1

a. Money

b. Shopping/material goods

c. Clothing/shoes

d. Makeup/hair/nails

e. Jewelry

f. Brand names, gifts, and valuables

g. Cell phone

9

7

2

1

1

0

1

13

4

4

1

2

5

1

12

6

4

2

3

4

1

Home and Transportation 2

a. Place to stay

b. Rides

1

0

0

1

1

1

Social Status and Opportunity 3

a. Social status/parties

b. Association with a gang

c. Doing stuff that older crowd or "adults do"

d. Modeling ads

1

0

2

1

6

1

2

0

6

1

4

1

Family Factors 4

a. Supporting the family

b. Family arranging marriage

c. Threat against family if not complying

d. Shaming by family if not complying

0

1

1

1

1

0

0

0

1

1

1

1

Substance Use 5

a. Drugs/alcohol 4 6 7

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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.
102

In their own words, 

“Well I'm aware that we've had some instances on our campus where young ladies have 

been approached by some male students to recruit them to work. Sometimes it can be 

very quick when a new female student shows up on campus, the male students who are 

doing the recruiting know exactly who they're going to go after pretty much once that girl 

shows up...It's almost accepted as normal in some circles, like, "that's just what we do." 

How we do things. Then there's also been a clear line between girls who are used as 

prostitutes and girls who are girlfriend material, or you know, girls over here maybe 

don't fit that but once they go in that direction they are treated and looked at differently. 

That's how it was explained to me by one.” (GUSD-01)

“There was also recruitment at the middle school level. So it was very young, it wasn't 

just our ninth or tenth grades. It was active recruitment, at the middle school level, as 

girls were walking home from school. I just remember the reporting, there was a van 

driving around campus, and there was a lookout for it. It's kind of...it was kind of eye 

opening at that time.” (SUHSD-03)

“It was a weird situation where I had to deal with CPS, but this was a parent who was 

very poor. Young daughter, she was a 9th grader, with a 20-something year old 

boyfriend. And I knew about it because she'd talk about it a lot. And this was the issue. 

Eventually this man moved in. And because he had money, he was paying the bills. Well 

that's fine, but here she has her 9th grade daughter sleeping with a 20 some year old man 

in her home. It's fine as long as the relationship worked. But then this is when I got to 

find out, that she didn’t want to sleep with him anymore. And her mom was saying... I 

was, I don't even have the right words! I was incensed, shocked. That's when I did my 

CPS report. And years later that young lady came back and thanked me. It's really... you 

don't realize sometimes the little things you do. And she said indeed, she felt that, that's 

what she said, she felt like a prostitute because her mom said he had to stay because we 

needed the money to pay the bills. So that's a very, I suppose that could be 

prostitution? The economy is so bad, and kids can’t find jobs.” (SUHSD-02)

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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.
103

“But both of these girls that we’re talking about – the parents were like I said, involved 

in the drug trade, and were kind of like loaned out to drug trade associates, and they 

would kind of roll around with them – they would cross drugs, they would you know, 

sleep with multiple people in the cell, in the group...the first one I ever heard of that was 

also when she was 8 she was given by a family member to a guy and released later, for a 

couple of months. But same thing – this girl’s dad was part of the drug trade – it was the 

same exact thing...[it was drugs] and ‘you can have my daughter for a little bit’ kind of 

thing.” (SUHSD-06) 

III.C.11 Staying In “The Life”

School staff mentioned numerous risk factors for continued victimization once in “the 

life,” including being enticed by an offer of drugs, money, material goods, or rides in exchange 

for sexual services (GUSD-01), being under a “pimp’s” control (GUSD-01), having commercial 

sexual activity as part of the family structure, or part of the “family business” (GUSD-01), a lack 

of social support outside of “the life” (GUSD-01) and difficulty breaking away from the guilt 

and shame and stigma attached (GUSD-01).

In their own words,

“When they get to a certain level of involvement, it's very, very difficult for them to pull 

away. And some of it is the fact that, especially if they're living still with their family, they 

can't... they're in their neighborhood. And it's the people in their neighborhood that in 

some cases...so it's very hard to get away from it. Even if they try to take the steps, and 

they're doing the therapy, you know, they try but it's almost like working with an addict. 

There are relapses. I can think of another student from one of our schools that came to 

us, and I had that knowledge when that student was coming here, and we saw some 

improvement, but then she ran away....She had kind of made the decision that that's what 

she wanted to do. It's very difficult for them to get out.” (GUSD-01)

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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.
104

Table 17. Incentives to Stay “In the Life”

Confirmed/

Suspected

Perceived #Schools

Proximity to 1 Others Involved

a. Connection/proximity to gang members in 

 neighborhood

b. Connection/proximity to people involved in 

 drugs/ prostitution

c. Gang members present at school

d. Part of family business

0

1

1

0

1 

1 

0

1

1 

2 

1

1

Threats and Coercion 2

a. Death threats if leaving gang

b. Under pimp control

c. Threats to family

2

0

1

0

1

1

1

1

2

Lack of Social Support 3

a. Guilt and shame 

b. Lack of social support outside of pimp

c. Don’t know who to ask for help

d. Lack of trust with law enforcement

0

0

0

0

3

1

1

1

2

1

1

1

III.C.12 Sex Trafficking Recruitment Tactics

Staff commented on the recruitment tactics of which they were aware. They mentioned 

numerous strategies used to entice students into commercial sexual activity, including offers of 

drugs, money, material goods, or rides in exchange for sexual services, demands of loyalty to 

family (parents and family members part of gang or are offering kids for money), the lure of 

higher social status, participation in a “rite of passage” for joining particular gangs or being 

invited to special parties with the “cool” crowd, filling the need for protection for youth without 

parental involvement and filling a general need for belonging.

In their own words:

“It was about 3-4 years ago, there was a documented gang. We were informed, probably 

not as much as maybe campus security might know, or maybe other people, but we were 

told that there was an active gang recruiting young ladies from our campus and that 

these ladies would be given you know, maybe phones, clothing, enticed, bribed with 

material items, and they would come to school at night and they would be pimped out. 

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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.
105

And they were actively looking...it was a Southeast gang. I do not remember the name of 

the gang. But they were arrested, I think. Arrests did happen. [So this would have been 

about 2010?] Yeah, 2009-2010. It was probably the first time I felt that "Wow, it’s 

happening at a high school level." I thought it was international type of thing, not 

necessarily domestic trafficking. Because you see on TV Thailand or India or something 

like that, not here in the neighborhood or at the school site.” (SUHSD-03)

“But um the question was how do we know. And it was direct reporting. But I also know 

in this case, that the student was- that wasn’t the situation. It was looking for a sense of 

belonging. And so the gang culture is what she found. And She really felt like that was 

her family. She had a family situation where she didn’t feel like she was getting attention 

where she wasn’t connected. So she truly felt like this was her family. And that this boy 

who had taken her in under his wing that was who she found the most sense of obligation 

to. So it’s a very vulnerable young child. A great kid beforehand and just got really swept 

up in it and then the drugs became a big piece of it.” (SDUSD-01) 

“When you were talking about the recruitment process, one student had shared that she 

was invited to go to a party and from there is where she met the pimp, or the person, and 

then was told to, that she could make money if she just went into this room, or whatever 

and she kind of felt- she was younger, she felt, she didn’t know how to say no, so she just 

kind of went with it. So that would be another way where a friend or person that they 

meet, whether at the hall or at a community, say ‘hey we’re going to a party’ and kids 

want to go to the party and feel accepted. But once at the party, whether they give them 

alcohol or any kind of drugs, it makes it easier for the pimps to influence them or 

encourage them.” (SDCOE-01)

“I don’t disagree with that, but one of the reasons I’m here is that I have a concern that 

that’s not going to address some of the root causes, and what causes shift in perception... 

girls get a lot of status, when they’re starting. I had a girl who joined a gang and she was 

very proud of that fact. Very proud. Most of the status she got was from being associated 

with that gang.” (SDUSD-05)

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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.
106

When we analyzed what potential indicators of sex trafficking are being reported most by 

high school staff, they included nine: (1) Use of multiple cell phones; (2) Markings, tattoos for 

gang membership; (3) Frequent use of restroom; (4) Student report of exploitation; (5) Sudden 

increase in material goods/clothing; (6) Frequent absences from school; (7) Inappropriate or 

provocative clothing; (8) Runaway from home, unstable living situation; and (9) Older boyfriend 

(18-25 years, a case of 40+ years).46

When asked what the challenges schools and programs face when helping students who 

have been recruited/victimized/exploited, the following responses were more typical. In their 

own words:

“...they get help when they’re with us but it doesn't seem like it's being addressed when 

they leave us. And they're going right back to the same thing. We give them counseling or 

SOS and then they go home, and first person they call is a pimp because that's the only 

person that's there for them. Even when we put them in programs, the guy will come out 

and pick them up outside.” (SDCOE-01)

“It's like, whatever issue that's being exploited to get them to prostitute, we don't have the 

resources to address. Whether it’s an emotional issue, a family issue, or a money issue, 

things like that - even after identifying- which isn't always identified, the main issue of 

why it's happening. We identify that it's happening, but on a deeper level, why are they 

being exploited? How are they allowing exploitation to take place? Those issues that 

pimp go after. We're not able to fill those holes.” (SDCOE-01)

(re: victims reporting to law enforcement) 

“I’ve personally spoken with someone who’s an identified CSEC victim and she says it 

often takes 10-15-20 times in contact with law enforcement before the victims are finally 

able to identify themselves as victims. So it’s a constant trying to build a relationship in 

order to gain trust in order for them to disclose that.” (SDUSD-12)

 

46 Some staff members commented on the challenges in discerning signs of trafficking from other 

culturally conditioned habits, e.g. some believed that Hispanic culture tends to normalize older boyfriends and made 

it difficult for female students to recognize or name their own victimization

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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.
107

In a few focus groups, staff gave encouraging stories of young people breaking away 

from “the life.” The following are samples of such stories.

(adapted from GUSD-01 transcript)

“We have had preliminary discussions at the district level, because we have not seen any 

victim get out and stay out long term. Whether that student is here or at any school in the 

district. Even if we've transferred kids for safety reasons, we haven't seem them get out 

and stay out because of the relapse, because of the dynamic. They might transfer and 

move away, so maybe that student...but when we see them, we don't ever see them say 

that life's behind me. With the exception of one, because she had unique support through 

our Camp Lead program over and over.

The Camp Lead program became her support system... she got adopted by about 20 

people. A [school official] took the role of surrogate parent one day, and helped her to 

enroll, because otherwise she wouldn't graduate. So I was here talking to her on a pretty 

regular basis, and when she [#1] came here it pretty much doubled the support she [the 

student] had. Plus all the people from camp...there was 15 people from other school 

sites, from schools she'd never attended, that showed up to watch her graduate. So that's 

a pretty unique situation, where we all loved the heck out of that kid. I would hope that it 

doesn't take 15 or 20 school employees every time to try and help one of these girls, but 

this kid garnered a lot of love. 

I think one of the things I learned from her in talking about it and having the 

conversation is that it's a cultural thing. It's what, that's all that was around her. I think 

that's part of the challenge. It did take that many people because the culture of it. 

Another group member asked, "How difficult was it for her to get out of the life?"

1 - Very. She, I would say she cried 80% of her camps for the first 5 camps. Because 

people were caring about her, she felt comfortable, she was so embarrassed. She had a 

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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.
108

religious foundation, so she was in conflict over what she was supposed to be, and who 

she was, and now she's not, and you know...

3- She was in my group during her second camp. I don't know that I saw her cry a ton. 

She didn't talk. I mean, she went, I'm just here. I just want to be here. That was all she did 

for that time. Every camp I went to, she was there. Every one. 

1- Now she helps run them. 

3- And, at some point, someone needs to decide that they're worth it. She decided she was 

worth it. She needed a lot of encouragement, and pushing and prodding to get her across 

that finish line, but you know, I think... I come to work every day, and #1 comes to work 

every day, with a lot of love in our hearts. She and I will run through a brick wall for any 

of these kids. And they have to want it, you have to want it. That comes back to selfworth. This particular kid had a foundation I think she could think back to. I don't know 

that all our kids have that foundation. I think, in order to change whatever it is, you could 

have all the support in the world, but until you decide you're worth it, that's a real hard 

time for the guilt and the shame that some of these girls feel... It's very difficult. 

5- I would agree that the key was she believed in herself.

1- Ultimately, she didn't for a long time. 

3- Even up to a month before graduation. There was still that conflict. 

5- But she would say that #1 would tell her that, over and over again. She heard it so 

many times that eventually she started to believe it herself.

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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.
109

IV. DISCUSSION

These findings have a variety of implications for San Diego County stakeholders to 

consider. The level of participation and support we received from San Diego stakeholders gives 

us even greater incentive to help the results of this project find a meaningful role in not just 

understanding the regional phenomenon, but also in guiding actions and policies that seek to 

reduce the scope and harm of this social problem for all involved. In this section we discuss the 

issues raised regarding the scope and nature of sex trafficking as it relates to gangs in San Diego, 

including the dynamics of facilitation and gang activity, the scale and nature of victimization as 

well as the role that schools and research might play in addressing this social problem. We 

discuss below the implications these issues have on policy for our region and beyond, and the 

implications this project has for future research. While there are a myriad of findings to be 

explored from this data in greater detail, here are our interpretations of some of the most 

significant findings:

IV.A Major Findings

1. The scale of the underground sex economy is considerably larger than that for which San 

Diego County has currently taken account or for which it is prepared given our perception 

of the level of county-wide awareness and resources dedicated to combatting sex trafficking 

at the conclusion of the study. At $810 million per year, the underground sex trade in San 

Diego measures as the second most lucrative illicit industry in the region, considerably 

behind drugs at $4.76 billion, and slightly behind the illegal trade in firearms at an estimated 

$920 million. San Diego’s underground sex economy rivals the income from macroeconomic forces such as the $800 million Otay Mesa Port of Entry (Department of 

Transportation, 2016) or the County’s entire, $900 million Natural Resources and Mining 

Sector (San Diego Economic Ledger, 2013). 

Facilitators were open about the lucrative nature of sex trafficking. They were also quick to 

make the connection between sex trafficking and drugs. The level of coincidence of sex 

trafficking and drugs makes us wonder what percentage of the $810 million profits from the 

underground sex economy is fuelling the $4.76 billion drug trade. Some current and former 

facilitators we circled back around to were skeptical of the $810 million estimate, 

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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.
110

wondering where all that money has gone since the “pimps” they know “aren’t living THAT 

large.” The regularity and expense of drug purchases for the maintenance of the habits of 

both facilitators and victims is likely one of the more dominant expenses toward which these 

profits are directed.

Significantly more attention and resources will need to be poured into identifying, rescuing 

and caring for victims of this crime. Increasing public awareness of the scope and nature of 

this problem may help direct much needed political will and resources to law enforcement, 

healthcare, social services and schools as the primary stakeholders that can enhance the 

county’s ability to reduce the scale and scope of sex trafficking in the region.

2. The scope of sex trafficking in San Diego County is wider than expected. Virtually no 

community in San Diego remains untouched by sex trafficking. Victims have been 

identified either living or ‘working’ in every city in San Diego County, and in areas of each 

that are both wealthy and impoverished. The degree to which sex trafficking seems to be 

moving online and off the streets means that commercial sex activities can be happening 

wherever facilitators have access to private spaces to operate. While most arrests for sex 

trafficking have happened at or near hotels in the county, and this does certainly seem to be 

a prime location, the results of this research lead us to wonder if hotels are overrepresented 

due to the relative ease of investigation compared to private apartments and homes, even 

gated communities as some facilitators noted. 

One hundred percent of the 20 schools where we did focus groups, spread across North 

County, Central San Diego, South Bay and East County, had evidence of sex trafficking 

happening connected to their students, while 90% had confirmed cases. As this was an 

exploratory part of our research, and given the logistical challenges associated with getting 

the participation of a wider range of school focus groups, we were unable to get a 

representative sample of county high schools. North County and East County were 

particularly lightly represented in this sample. Our responses in the focus groups were 

further limited by the relative lack of knowledge in general about sex trafficking and its 

indicators. School officials across most of San Diego County’s school districts were, at the 

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.
111

time of the writing of this report, rolling out human trafficking education to an increasingly 

wider range of school staff. We suspect that if we were to repeat this study a couple of 

years from now that we would be welcomed into a wider range of schools with a deeper 

level of awareness on average. We suspect that this increasing level of awareness will also 

lead to an increase in the number of cases referred on to law enforcement and social 

services.

While we found evidence of victimization happening all in a wide range of neighborhoods, 

ten zip codes are home to a disproportionate number of victims. These zip codes correlate 

with underserved populations that deserve special attention. As the county prioritizes where 

to spend scarce resources on awareness, prevention and related services, we encourage the 

county to start with the schools and social services in these neighborhoods, but to include 

such efforts in a strategic countywide effort that eventually touches all neighborhoods. 

3. We have identified 110 gangs, sets and cliques in San Diego County from a wide variety of 

neighborhoods and racial/ethnic backgrounds that have members that are engaged in 

profiting from sex trafficking in San Diego. The level of centralization and organization of 

sex trafficking activity in the gang varies significantly from cliques and sets that 1) loosely 

associate with the gang for protection while they act independently, and 2) those that have 

centrally organized units with a centralized taxation system to 3) those with linkages to 

transnational criminal networks. As we have no baseline, we cannot judge quantitatively 

whether this is an increase or decrease from the past, but both the sex trafficking facilitators 

and the law enforcement officials we interviewed agree that this is a growing income for 

San Diego area gangs. 

More specific measures of change over time are needed to understand this phenomenon and 

to address it from law enforcement and social service perspectives. The leadership of the 

San Diego Commission on Gang Prevention and Intervention run by the Mayor’s Office of 

the City of San Diego has been instrumental in helping us gather and interpret the data from 

this current study. We recommend that the Commission continues to monitor sex 

trafficking as one of the crimes they monitor related to gangs in the region and that they add 

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.
112

quantitative measures that in the future could be compared to the results of this study to get 

a sense of the change over time. As the central keeper of wisdom on all things gang-related 

in the community, and as an important mediator between the community and law 

enforcement, we recommend that the Commission on Gang Prevention and Intervention be 

empowered to sponsor such research in the future. 

4. As the likely first point of contact for victims of sex trafficking, for a variety of reasons law 

enforcement lacks sufficient information to correctly distinguish victims of sex trafficking 

from other related crimes (e.g. prostitution, domestic violence, sexual assault). Further 

support to this concern is added by our analysis of law enforcement officer incidence reports 

related to domestic violence that lead us to approximately 120 cases per annum that we 

would advise law enforcement to investigate more deeply on suspicion of sex trafficking. 

Under law enforcement systems that treat victims of sex trafficking first as criminals and 

second as victims, we believe law enforcement is less likely to be trusted with information 

from victims that would help them identify victimization. Even the most careful and trusted 

victims service agencies know that much of the information we need to identify sex 

trafficking victimization happens not on first intake but in the interviews and conversations 

with trusted staff once in their care for some time. 

Our finding that 50% of those arrested for prostitution related charges were at one point in 

their lives in fact sex trafficking victims suggests that the system (law enforcement, social 

services, schools, etc.) is not yet fine tuned enough to identify sex trafficking victimization 

at a sufficient scale. Providing greater training on indicators and protocols for those who 

have first contact with potential victims, including law enforcement, emergency medical 

personnel, all social service agency personnel (particularly those that care for women and 

girls) and school staff will go a long way to increase victim identification. 

We also believe that the county would benefit from widespread training on the indicators of 

sex trafficking and how such indicators relate to or differ from indicators to related social 

problems so that parents, guardians and others who are responsible for the deeper care of 

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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.
113

potential victims have a greater chance of identifying when the ones in their care of 

vulnerable to sex trafficking. We encourage the county to spend concentrated resources on 

human trafficking training for those in the child welfare and foster care systems in 

particular, as well as all those who work with runaway and homeless youth.

5. Further evidence for the need for greater examination of the connections between law 

enforcement, schools and social services comes from our findings that the median age at the 

time of a first arrest for prostitution is 19 years old while the average age of entry into sex 

trafficking is 16.1 years of age. Noting that our “age of entry” estimate is conservative, this 

means that community leaders are unaware of the average victim being trafficked for about 

three years before they reach the attention of law enforcement or social services. Law 

enforcement and social service agency personnel are aware of this gap and are working to 

close it. The relatively recent shift to educate school staff across the county should help in 

this regard. Our research suggests that special attention should be aimed at those who work 

with middle school and early high school girls, particularly but not exclusively for those 

who work in socioeconomically disadvantaged neighborhoods. 

An area in San Diego that seems underexploited as a resource for victim identification is the 

healthcare sector. Widespread CSEC training of emergency personnel and other health care 

providers that work most specifically with juvenile girls would help spread the net of 

identification beyond those more likely to come into contact with law enforcement and 

social services in a way similar to that of schools. Particular attention to training all staff in 

public health clinics would increase the likelihood of identifying sex trafficking 

victimization among those most vulnerable. 

6. The stereotype that sex trafficking is principally a practice of black gangs is inaccurate for 

San Diego County and may channel apprehension efforts by law enforcement in too narrow 

a direction. The highly visible social media presence of African American gangs on social 

media make them “low hanging fruit” for law enforcement investigations and, importantly, 

need no less attention from law enforcement. But they are not the only subpopulations 

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.
114

involved. 

Law enforcement and facilitators confirmed the widespread assumption that Hispanic street 

gangs are not thought of as prime participants in sex trafficking. But we found that many 

Hispanic gangs and gang members actually do participate in sex trafficking. Some do so in 

a highly organized fashion, and some in purely entrepreneurial ways.

Our sample of facilitators was strongest for white, black and Hispanic gangs. Numerous 

conversations with law enforcement and facilitators lead us to believe that much research 

remains to be done on Asian gangs and their unique types of facilitation. While not the only 

other sub-community where sex trafficking related to gangs is reportedly happening, 

specific concern about trafficking at scale was mentioned in our interviews with facilitators 

as related to Asian street gangs, illicit Asian small businesses such as massage parlors as 

well as some mention of organized crime.

Although a wide variety of gangs are involved in sex trafficking, many are loosely 

networked making them difficult to identify and track. A lack of a centralized command 

and/or taxation system makes the investigation and prosecution of sex trafficking as a 

business more difficult to track. The three major cases of gang related sex trafficking 

prosecuted in San Diego since 2011 were all prosecuted under the Racketeer Influenced and 

Corrupt Organizations (RICO) law, with law enforcement connecting the actions of all 

involved to a central organizational structure, a “gang.” While this research confirms gang 

involvement in sex trafficking, the relatively entrepreneurial, diffuse and non-centralized 

nature of that involvement that we found may make it difficult for law enforcement to use 

the RICO statute to capture the bulk of sex trafficking activity in San Diego County.

7. The world of sex trafficking as it relates to gangs is extremely complex and changing, with 

the structure and function of gangs shifting and morphing and facilitators playing a variety 

of roles. The majority of facilitators in our sample reported relying less on physical 

coercion than on exploitation of socioeconomic conditions vulnerability, prior abuse in the 

home, drug addiction, and mental health issues. While it is likely that a certain level of 

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.
115

Vicious-Violent sex trafficking is underreported given our methodology, we feel that this 

underreporting does not match the disproportionate attention that “gorilla pimping” gets in 

the media and some of the awareness training put on by law enforcement and victims 

services alike. 

This does not mean that highly coercive networks and organizations are not a major threat in 

our region, but the majority of sex trafficking activity identified in our interviews was 

dependent on skills to psychologically manipulate and coerce another person into sex for 

profit. And we have no interest in downplaying the seriousness of this level of viciousness 

and want and end to all such victimization. But a disproportionate amount of attention on 

the more sensational aspects of trafficking may lead to disproportionate responses from both 

law enforcement and victims services. Recognizing that psychological manipulation is the 

core strategy of sex trafficking recruiters in San Diego gives those training potential victims 

and their supporters a place to focus resources and trainings more appropriately.

8. If we take the perspectives of the facilitators we interviewed seriously, youth, particularly 

teenagers, are being recruited into sex trafficking at rates previously unseen by older 

facilitators. A common refrain from facilitators is that the age of the up and coming 

facilitators is getting younger and younger. As can be seen from our victims data, the 

average age of entry into sex trafficking is 16.1 years of age, and likely even younger on 

average. A central reality seems to be that our children and young adults are trafficking our 

children and young adults. 

The facilitators we interviewed were well aware of the RICO arrests in San Diego county in 

recent years and the increasing scrutiny related to sex trafficking from both law enforcement 

and in the media. They did not seem to think that this increased scrutiny would deter the 

amount of sex trafficking happening, centrally because of how lucrative it has become and 

how relatively difficult it is to prosecute. But conversations with facilitators led us to 

wonder if one reason this activity will remain high despite the visible prosecutions is that if 

it is a growing habit of young people to commodify one another for sex, the public debate 

over which laws, penalties and social services are most important will have to shift to meet 

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.
116

this reality. At the same time, the results of this study would suggest that any shift to 

identifying and prosecuting young facilitators should take heed not to limit investigations to 

those population groups stereotypically involved.

IV.B. Policy Implications

Given the findings of this project, the participating researchers make the following 

recommendations to the San Diego County Regional Advisory Council on County Human and 

Child Sex Trafficking. The following recommendations can be sorted into three categories: 

capacity building, service delivery, and new programming.

Capacity Building: Specific actions can be taken to engage in capacity-building efforts and

to strengthen institutions on the ground, including bolstering the training of officials and 

frontline practitioners to enhance their engagement with communities.

1. Conduct assessments of local drivers of CSEP: Risk assessments and perception studies 

help people better understand the local drivers of vulnerability specific to their 

communities, and are key to providing baseline data to track the impact of counter human 

trafficking programming, and then drawing on those lessons to inform future 

programming. 

2. Expand and regularize CSEP training for frontline officials and practitioners: Human 

trafficking is just coming into the formal training systems of frontline officials and 

practitioners. Practical trainings should be conducted for all frontline officials and 

practitioners - on both sides of the border - who engage with groups of people who are 

vulnerable to recruitment into CSEP by gangs, those who are vulnerable to recruitment 

into facilitating CSEP, and those in both categories who have already been recruited. 

While front line law enforcement agents and officers are just being brought up to speed, 

and the social workers of the San Diego County Child Welfare Services are just being 

given new CSEC protocols, San Diego County should increase resources for the training 

of school personnel in identifiers and protocols, as well as awareness training for students 

from middle and high schools. San Diego would also do well to expand the trainings for 

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.
117

healthcare professionals in the indicators and protocols. Given its prominence and social 

impact in San Diego, special concern has been raised in this study for increased 

awareness training for the military in all its facets. 

3. Support Robust Community Policing: This study represented the first two steps 

(SCANNING AND ANALYSIS) of the SARA model of problem-oriented policing 

(Goldstein, 1979; Goldstein, 1990). The next two components - Response and Evaluation 

- require robust community policing - a philosophy that supports police-community 

partnerships and joint problem-solving - to encourage two-way information sharing and 

joint public safety initiatives. Community policing offers an opportunity to build trust and 

partnerships in communities that can help police protect against the criminal sexual 

exploitation of its members. 

Service Delivery: The following recommendations involve specific actions to improve 

service delivery to victims of commercial sexual exploitation, and to deter would-be 

perpetrators. 

4. Increase support for victims and survivors: Supporting victims and survivors of CSEP is 

an imperative principle of justice, and San Diego is encouraged to expand rehabilitation 

of and support for victims of sex trafficking. Three issues are critical. 

4a. Eliminate existing ordinances that criminalize “child prostitution” and replace 

with laws that protect them as victims

4b. Address the shortage of facilities for victim-survivors. The County has just 29 

beds for rescued sex trafficking victims. None of them serve men, and none of 

them are human trafficking specific beds for minors.

4c. Regularize collaboration between and among victim advocates and law 

enforcement as a measure to recognize and protect victims. 42% of 647b arrests 

may in fact reflect cases of trafficking victims, and their safety, privacy, and 

physical and psychological well-being should be ensured.

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.
118

5. Amplify Survivor Voices: Amplifying the voices of victims and their stories can also 

contribute to exposing the brutality and hypocrisy of pimps, facilitators and their 

narratives. Survivors and family members can be powerful changemakers. 

New Programming: The following recommendations regard specific enhancements within 

security and criminal justice sectors, and introduce disengagement and reintegration 

programs.

6. Prison-based Rehabilitation Interventions: San Diego County should develop prisonbased rehabilitation interventions for incarcerated facilitators, and programs to assist 

individuals who are at risk of being recruited into facilitation. 

7. Intentional Interface with Gang Intervention Programming already in place: San Diego is 

home to the Commission on Gang Prevention and Intervention, a network similar in 

diversity of membership to the HT Advisory Council. Its purpose is to prevent gangrelated violence, to disengage at risk youth, and to build relationships between vulnerable 

communities and San Diego governmental and law enforcement officials. The 

Commission has several time-tested programs that are natural entry points for engaging 

facilitators and those at risk of becoming involved. We strongly recommend and support 

working with former “pimps” and facilitators to foster disengagement and reintegration 

programs. 

8. Expand apprehension and prosecution efforts to buyers: If growing attention in San 

Diego is being paid to the sellers (facilitators) and the persons as products being sold in 

San Diego’s sex trafficking market (victims), little policy and infrastructural attention is 

being given to curbing the demand (buyers). The disincentives for buyers are relatively 

inconsequential and the facilitators argue that they are just filling a market demand. We 

recommend both stronger policy addressing demand and public awareness campaigns to 

make the broader public, especially potential buyers, more aware of the true costs of the 

underground sex economy in San Diego

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.
119

IV.C. Future Research

Collaborative Research: The results of this research make a strong case for building 

national databases from the ground up, funding researchers with local and regional expertise to 

develop partnerships across the sectors needed for access to data and the populations to be 

researched. The partnerships we nurtured through our involvement in the San Diego County 

Regional Advisory Council on Human Trafficking and CSEC helped us 1) address research 

questions that are most pressing to those working to raise awareness, curb sex trafficking 

activity, intervene with gangs, and rescue/rehabilitate victims, 2) gain access to databases and 

populations that in the case of sex trafficking research would otherwise have remained hidden 

and 3) have the most likelihood of impacting public policy and infrastructure for positive change. 

National policy will be strengthened by the comparative application of lessons learned from the 

most robust local and regional measures.

Scale: The surprising scale of the underground sex economy in San Diego demands 

continued refinement of regional empirical measures of the illicit sex economy, triangulating 

findings from other sources, tracking change over time and greater attention to disaggregation of 

sex trafficking activity from the rest of the illicit sex economy. The range of CSEP reported in 

Section is extremely large, ranging from 2,600 to 17,617. Refinement of local estimates requires 

analysis of case files to disaggregate human trafficking cases from other offenses. It also requires 

inclusion of Federal data. Continuing to both deepen the research partnership with local law 

enforcement agencies, and widen the partnership to include Federal data not captured in this 

study, is of paramount importance going forward. 

Gangs: We consider this research a baseline empirical analysis of the relationship 

between gangs and sex trafficking in San Diego County. While 110 gangs were named in this 

research, data on each of these gangs was received from a small number of persons in each gang. 

Future researchers can build a more ethnographically rich profile from a wider representation of 

each of these gangs in order to better understand the changing dynamics and significance of gang 

life in San Diego County. 

Cooperation with San Diego’s Commission on Gang Prevention and Intervention has 

been indispensable for understanding and interpreting findings from our interviews with current 

and former gang members. To the degree that our research worked independently of the 

networks established by those already doing work related to gangs we were able to add 

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.
120

substantive insight into the the law enforcement, social services and faith related groups who 

currently are the most knowledgeable and engaged actors related to gangs.

Law Enforcement: The collaborative nature of San Diego’s movement to address human 

trafficking combined with the legitimacy that funding from the National Institute for Justice to 

give researchers on this project broad and trusted access to non-public data from a wide variety 

of law enforcement agencies in San Diego County, the Sheriff and the San Diego Police 

Department in particular. Through this level of access we were able to compare measurements 

and findings across jurisdictions, something that during the course of our research our regional 

law enforcement agencies were working to improve. The dialogue between our research team, 

law enforcement analysts and community based-researchers helped to develop greater insight 

and more refined empirical measures for each of our respective roles.

Social Services: As many who research sex trafficking from the perspective of social 

services know, the standardization of measures that identify sex trafficking victims is a work in 

progress. This research extends the regionally vetted research done by the Vera Institute in New 

York by field testing a portion of the standardized Trafficking Victim Identification Tool they 

developed here in San Diego. The eight social service agencies found parts of the tool helpful, 

and other parts they wanted to modify. The research raised debate about and helped to refine 

where in the intake process such tools are best administered. While still in process as of the 

writing of this report, the network of social service agencies that collaborate under the Victims 

Services umbrella of the San Diego County Regional Advisory Council on Human Trafficking 

and CSEC are using this research to outline a regionally appropriate intake assessment tool.

Schools: The most exploratory part of our research was the focus groups we conducted in 

20 high schools across San Diego County, spread across Central San Diego, the South Bay, East 

County and North County. Drawn from a purposive sample rather than a random sample that 

would allow us to extrapolate the findings with confidence across the region, the scope of 

trafficking found related to school and school children was nonetheless surprising and demands a 

more systematic analysis of the sex trafficking activities related to our schools. Having 

identified what school officials think is happening at their schools, a strong follow up research 

project would be to collect data from the students themselves. 

One path toward collecting data from students we’d recommend is to add questions about 

sex trafficking to standardized student response surveys that already are in use. For example, 

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.
121

California already has a strong student feedback system through their Healthy Kids Survey 

conducted by WestEd for the California Department of Education. We recommend the 

California Department of Education add a “human trafficking module” to the set of questions 

they ask students, much like the “gangs module” they currently employ.

In part from mid-stream information coming from our study and our ongoing dialogue 

with school officials, San Diego county school are in the process of developing systems to roll 

out sex trafficking education first to all key staff members in county schools, then to students 

through locally and developmentally appropriate awareness curriculum at the student level. 

Informally our findings helped to identify which staff members on average were better informed 

on CSEC (e.g. counselors, campus security and upper level administrators) and pointed to the 

need for greater information on indicators (how to identify) and protocols (what to do once 

identified) to spread across all staff in all schools across the county. 

Social Media Analytics: Social media analytics methods are capable of effectively 

detecting, identifying, tracking, and monitoring the ongoing communications, interactions, 

activities and operations of criminal gangs in the U.S. and Mexico. The approach to research 

requires a clear recognition of the opportunities and constraints of monitoring social media. 

When pursued cautiously and mindful of biases, it can usefully supplement ongoing 

investigations into the domestic and transnational dynamics of cartel and gang activities. 

However, meta-analysis alone is insufficient, and any future research must be supplemented with 

digital forensics and especially content and behavioral analysis of gang member profiles and 

related networks. 

Collaboration among researchers: An important practice and outcome of this project has 

been the regular interaction of a network of regionally based researchers studying various aspects 

of human tracking. As co-chairs of the Research and Data Subcommittee of the San Diego 

County Regional Advisory Council on Human Trafficking and CSEC, the study’s investigators 

hosted quarterly gatherings o 

f other university-based researchers, graduate students, law enforcement analysts, social 

service research experts and community-based researchers to collaborate on various dimensions 

of research. 

The San Diego County Board of Supervisors saw such value in the collaborative 

gathering of researchers we were modeling that they decided to fund what we called HTThis 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.
122

RADAR (Human Trafficking Research and Data Advisory Roundtable), i.e. the ongoing 

coordination of county-wide human trafficking research. In late 2015 HT-RADAR was 

showcased by San Diego County leaders to the statewide Blue Ribbon Commission on Human 

Trafficking run by the HEAT Institute. Our final recommendation is a call for private/public 

partnerships to continue and increase research funding to develop more detailed and more robust 

local and regional findings, but also for the regional coordination of these efforts to help improve 

the focus, efficiency and impact of such research efforts.

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.
123

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142

VI. TABLES AND FIGURES 

47 Table 1: TVIT Implementation 

48 Table 2. Human Trafficking Predicate Crimes 

55 Table 3: Approximate In-Depth Interview (IDI) Response Rate 

59 Table 4: Cash-to-GDP Ratios and Total Cash Stock Estimates for San Diego 

61 Table 5. The four modeled sectors and their composite variable proxies with sources 

79 Table 6. Distribution of Human Trafficking Cases 

80 Table 7: Percentage of FFE Participants Meeting Legal Definition of Past or 

Current Trafficking 

81 Table 8: 40 trafficked victims out of 80 total cases of FFE and TVIT data combined 

85 Table 9: Combined Arrests & Booking for Human Trafficking Predicate 

Crimes 

86 Table 10: Revised Estimates of Arrests of Trafficking Facilitators 

88 Table 11: Prostitution, Soliciting and Loitering Arrests 

89 Table 12: Age at Intake from SSP8 Data 

91 Table 13. Age of Adult Survivors at Time of Arrest vs. Age of Entry 

92 Table 14. Zip Codes 

98 Table 15: CSEC Risk Factors 

100 Table 16: Summary Data on Incentives for Recruitment to CSEC 

103 Table 17. Incentives to Stay “In the Life”

FIGURES 

62 Figure 1 Figure 2. Estimated Sizes of Components of the San Diego County Cash 

Economy, 2000-2014 

92 Figure 2 – Ethno-Racial Profile of FFE Adult Dataset 

93 Figure 3 – Countywide Location of Individuals at Time of Arrest 

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.
143

VIII. APPENDICES 

VIII.A INTERVIEW PROTOCOL FOR FACILITATORS 

VIII.B GLOSSARY OF TERMS 

VIII.C GANG STRUCTURE ANALYSIS 

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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.
144

APPENDIX A: INTERVIEW PROTOCOL FOR FACILITATORS 

Date of Interview: 

Interviewer Name: 

Time at Start of Interview: 

Involvement in Pimping/Trafficking 

List Experiment Questions:

I will ask you a list of 5 activities, which you may or may not have done before. When I 

finish the list, please tell me the number of activities you have experienced. Note, do not tell 

me if you have done each activity, just tell me HOW MANY of these things you have done or 

are true for you. 

[control – YES] 

1) How many of the following activities have you done or are true for you? 

- I have gotten more than one tattoo

- I never drink soda

- I have been paid money by a prostitute (Sensitive question will be dropped from 

control group)

- Drove a car at a speed of more than 100 miles per hour

- I have at least TWO (2) siblings.

2) How many of the following are true for you?

- I am right handed.

- I would consider myself to be a sports fan

- My shoe size is over 9

- I have had sex with a prostitute (Sensitive question will be dropped from control 

group)

- I follow a religion

1. Has a prostitute ever paid you for a particular service? [Formerly: Have you ever 

been involved in the pimping out of girls?] 

[If yes] Can you tell me how you got into it? 

If no, ‘Have you been involved with a group that did’. 

[If yes] How did you get them to join the game or the life? 

a. What were your motivations for joining the game/life? [Probe for preferred 

‘classification’ of activities, e.g. ‘pimping,’ ‘prostituting,’ escorting’, etc]

2. How important is pimping/prostitution in making money for your gang/group? [If 

no, Probe: 

a. “What are the most money making activities for your group? Where does 

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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.
145

pimping fall?” Then a list:

#1 Lucrative: 

#2 Lucrative: 

#3 Lucrative: 

3. When did your group become involved in prostitution? 

4. What is the average age of a pimp? What is the average # of years a person needs to 

be in the gang in order to become a pimp? 

5. What’s the average age of a prostitute/sex-worker? 

5b. What age is too young to be a prostitute? 

5c. What age is too old to be a prostitute? 

6. In your experience, how old was the youngest girl or boy you saw working the 

streets? 

7. How old were you when you got into it? 

8. Do gang leaders direct the prostitution operation, or is it managed by individuals 

within the gang? E.g., does the whole gang profit? 

a. How does that work? Does the pimp get a cut and the gang get a cut? 

b. Does the girl get a cut? 

9. How long do pimps/girls stay in any one place? (Or: How often are the girls moved 

between locations?) 

10. Do you know/remember the locations? [Probe: Is there a specific order, like San 

Diego, then LA, then...? Probe: Do the pimps come back to a specific location after 

awhile, or are they always working out of new places?]

a. Does the pimp move/transport you/the girls himself, or is somebody else 

responsible for doing this? 

b. Do pimps ever move girls out of San Diego for their activities? Out of California?

c. Do they ever recruit girls from out of San Diego? Out of California? If so, how do 

they usually do this recruiting?

d. Do you know if people recruit girls out of high schools? Middle schools? 

[alternate order]

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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.
146

11. Are there any rivalries between groups involved in pimping? (E.g, over 

streets/corners, hotels, neighborhoods)

12. What number of members would you say are involved in pimping activities? So 

what percentage is that? Probe: 

a. Think of your 5 closest associates. How many of those 5 associates are 

involved in pimping/prostitution activities? 

13. Did/do you/have financial quotas to meet? What were they? 

14. Think of an average pimp. How many girls is he directly responsible for? 

15. Think of a successful pimp. How many girls is he directly responsible for? 

16. Think of a pimp who is barely scraping by/barely making it. How many girls is he 

directly responsible for? 

17. What do you think are qualities that make a girl more lucrative? 

18. What is the average a girl takes in (gross) per week? 

19. What is the average a pimp takes in (gross) per week? 

20. Can you talk to me about the johns involved in these activities? To your knowledge, 

what is the average age of a john? 

a. Are they mostly from a particular race or social class? 

b. Do sex workers ever see the same john on multiple occasions? If so, do the johns 

develop a relationship with a specific sex worker or do business with a specific pimp? If 

there is an ongoing business arrangement with the johns, how is this relationship 

maintained and business coordinated?

21. Do you work [collaborate/cooperate?] with anyone outside of the gang/group in re: 

pimping/prostitution? Who/how does that work? 

a. Probe: When/if you collaborate, what is the average sized (or maybe perfect 

sized) group? 

22. Do you ever work [collaborate/cooperate?] with other gangs in 

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147

prostitution/pimping[-related activities?] 

a. What is the average number of people involved in a single trafficking 

transaction.

23. Do you work [collaborate/cooperate?] with anyone in Mexico [with regard to] 

pimping/prostitution? How does that [relationship] work?

24. How do you try to keep pimping out of the view of police? 

a. What is the most successful method? 

b. What is the least successful? (Define successful as getting caught by the 

police) 

25. How many business owners do you know? 

How many pregnant women do you know? 

How many ‘Veronica’s do you know? 

How many pimps do you know? 

How many girls in the life do you know? 

How many teachers do you know? 

How many auto mechanics do you know? 

How many ‘Jose’s do you know? 

How many gun dealers do you know? 

Probe: Which cliques/set/crews do those pimps/gun dealers come from? 

26. How did you keep arms-trafficking out of the view of police? 

a. What is the most successful method? 

b. What is the least successful? (Define successful as getting caught by the 

police) 

Gang Characteristics 

27. What is your best estimate for how many members are in your group? [IF 

UNKNOWN, “How many gang members where in your group last time you knew?] 

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148

28. Age range: 

c. What age did you join the group? How many years were/have you been a 

part of the group?]

d. Think of the youngest person to have ever entered your group formally. How 

old was s/he? 

e. Think of the oldest person who was in or is currently in your group, how old 

is s/he?”

29. Is your gang [clique/crew?] all of the same race/ethnicity? If not, what % 

other/specify. Has it always been that way, or did this change over time? 

30. Think of your 5 most important associates when you first entered into your gang. 

How many were directly involved in pimping? 

31. Think of your 5 most important associates today. How many are directly involved in 

prostitution-related activities like pimping? 

32. Does your gang/group work with/partner up/have alliances with other 

gangs/groups? What activities do you cooperate on?] 

33. Were you ever ‘promoted’ within your group? How does one get promoted/acquire 

responsibility over others? How does one get promoted/acquire responsibility over 

group activities?]

34. How did your gang/group obtain its firearms?

a. Gun / outdoors stores 

b. Pawn brokers 

c. Gun fairs 

d. Black market / person-to-person sales 

e. Other gangs [Which ones] 

f. Other 

How did your gang/group obtain its ammunition? 

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149

a. Gun / outdoors stores 

b. Pawn brokers 

c. Gun fairs 

d. Black market / person-to-person sales 

e. Other gangs [Which ones?] 

f. Other 

[If respondent indicates weapons/ammunition were received from the military] 

Probe: From which branch of the military? How are the weapons acquired - can you 

describe that process for me? [IF these are necessary: Who coordinates these 

activities on the military side? On the gang/group end? Do you request or seek out 

specific types of firearms/ammunition, or do you just take what you can get?

35. Does your gang/group have open hostilities with other gangs/groups? Is there any 

activity or situation that you would cooperate on?] 

36. Think of El Cajon Blvd 5, 10 years ago Was there any inter-gang violence on that 

blvd then? If so, when did that stop? Did someone initiate it? 

REFLECTION 

37. We have asked you a number of questions. Thank you for your participation in our 

research. As we are finished asking you questions, do you have any questions for us? 

Time of End of Interview: 

[Interviewee’s Group name:_______________________ ]

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150

APPENDIX B Glossary of Terms 

TERM/VARIABLE DEFINITION SOURCE (if applicable)

Commercially Sexually 

Exploited Persons (CSEP)

This term refers to all persons, regardless of age. CSEC 

is a subcategory.

Commercial Sexual 

Exploitation of Children 

(CSEC)

Commercial sexual exploitation of children is the 

exploitation by an adult with respect to a child or an 

adolescent – female or male – under 18 years old; 

accompanied by a payment in money or in kind to the 

child or adolescent (male or female) or to one or more 

third parties.

International Labour Organization: 

http://www.ilo.org/ipec/areas/CSEC/lang

Facilitator of Sex 

Trafficking (FST) Refers to the person/s facilitating CSEP

Sex Trafficking Federal law, through the Trafficking Victims Protection 

Act, defines trafficking as:(1)“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;” 

Trafficking Victims Protection Act (TVP

http://www.state.gov/j/tip/laws/

Commercial Sexual Activity Sex acts for compensation (monetary, other)

People in the Commercial 

Sex Economy (PCSE) 

Refers to Commercial Sexual Exploitation (high on 

coercion) and Commercial Sexual Activity (lower on 

coercion)

Agents of CSEP A classification system that acknowledges both agency 

and exploitation. Among Agents include Facilitator, 

Survivor, Thriver, 'Pimp', etc

Human Trafficking Federal law, through the Trafficking Victims Protection 

Act, defines trafficking as:(1)“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;” or (2) “[T]he 

recruitment, harboring, transportation, provision, or 

obtaining of a person for labor or services, through the 

use of force, fraud, or coercion for the purpose of 

subjection to involuntary servitude, peonage, debt 

bondage, or slavery.”

Trafficking Victims Protection Act (TVP

http://www.state.gov/j/tip/laws/

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151

Gang We adopt John Hageorn's working definition: "Gangs 

are organizations of the street composed of either 1. the 

socially excluded or 2. alienated, demoralized, or 

bigoted elements of a dominant racial, ethnic, or 

religious group. While most gangs begin as 

unsupervised adolescent peer groups and remain so, 

some institutionalize in barrios, favelas, ghettoes, and 

prisons. Often these institutionalized gangs become 

business enterprises within the informal economy and a 

few are linked to international criminal cartels. Others 

institutionalize as violent supporters of dominant groups 

and may devolve from political or conventional 

organizations. Most gangs are characterized by a 

racialized or ethno-religious identity as well as being 

influenced by global culture. Gangs have variable ties 

to conventional institutions and, in given conditions, 

assume social, economic, political, cultural, religious, 

or military roles."

Hagedorn, John: 

https://www.uic.edu/orgs/kbc/Definitions

Survivor Persons who have exited the situation of having been 

subject to sexual or labor exploitation as a result of 

being tricked, lured, coerced, or forced into a vulnerable 

situation by traffickers

Adapted from Ascentria Care 

Alliance: http://www.ascentria.

org/legal-help-for-survivors-ofhuman-trafficking

CONTINUUM OF 

COERCION

Social Possessiveness 

Coercion (SPC) Defined as a composite of 5 grades of force designed to 

induce compliance and intimidation

Psychological Coercion 

(SPCPsychological)

Refers to (1) Social and emotional isolation (2) Induced 

emotional exhaustion (3) Monopolization of 

perceptions (4) Reinterpretation of reality (5) 

Degradation, including humiliation, denial of the 

victim's power, and name-calling (6) The powerful 

intermittent reward schedule: Occasional indulgences 

that keep hope alive that the abuse will cease. Examples 

include “Selling a dream”; using love as a tool to 

manipulate; using derogatory terms for sex work; 

handing money to pimp faces up; walking behind pimp; 

threats of ‘exposing’ sexual deviance to friends/family 

(i.e., ‘slut shaming’)

Adapted from BIDERMAN'S 

CHART OF COERCION. 

Amnesty International, 

Report on Torture 

(New York: Farra, Strauss, and 

Giroux), 1973. 

Sexual Coercion 

(SPCSexual)

Includes both rape, and sex acts with CSEP

Chemical Coercion 

(SPCChemical)

Altered states of consciousness: Providing drugs; or 

Forcing drugs

Physical Coercion 

(SPCPhysical)

Physical violence (beatings, slaps, punches)

Economic Coercion 

(SPCEconomic)

Greater than 30% of earnings taken by facilitator

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152

GANG 

STRUCTURE

Rules (RLS) Reference to written or unwritten rules including: 

(a) appropriate gang colors and attire;

(b) roles and duties delineated to members;

(c) ownership of turf and how that turf is to be 

protected;

(d) which gangs are rival gangs and why those gangs 

have become

enemies.

Size of Gang (SG) Number of members as described by respondent

Intergenerational Gang 

(IGG)

Represented in the age range of members as described 

by respondent

Complexity (CX) The sum of positive responses to the following 11 

structural and behavioral characteristics

Ruble and Turner (2000): 

http://www.hawaii.edu/hivandaids

/A_Systemic_Analysis_of_the_

Dynamics_and_Organization_of_

Urban_Street_Gangs.pdf; and 

Spindler and Buchard (2011): 

http://icj.sagepub.com/content

/21/3/263.abstract

 CXD - Duration Age of gang as described by respondent 1=10 

 or less, 2=25 or less, 3 = over 25, 4=over 40

 CXT - Territorial Statements expressing turf rivalries

 CXS - Ind. 

 Specialization

References to individual members pursuing a 

particular line of work according to preference 

(drug dealer, pimp, arms trafficker, enforcer)

 CXR - Role 

 Differentiation

References to proscribed roles played by gang 

members (e.g. enforcer, driver, look out)

 CXSG - Subgroups Respondent belongs to a subgroup of known 

gang, or describes subgroups (cliques, sets, 

crews, groups)

 CXP - Promotion Whether formal promotion within the gang is 

possible

 CXTS - Tax Structure Whether profits are distributed (e.g. taxes paid 

up the hierarchy)

 CXL - Leader References to a leader or leadership structure

Undirected Facilitation (UF) Individual activities not dictated by, nor 

directly profiting, the gang

Directed Facilitation (DF) Individual activities dictated by, and directly 

profiting, the gang

Behavioral Market Types 

(BMT) 

References to organized behavior in pursuit of 

monetary gain derived from illegal activity.

 BMT - Drugs References to drug sales, trafficking, or use

 BMT - Sex References to CSA, and CSEP

 BMT - Theft References to robbery, theft, stealing

 BMT - Arms References to arms purchases, sales, and/or 

trafficking

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153

 BMT - Human Smuggling Refernces to the importation of people into a 

country via the deliberate evasion of 

immigration laws (ICE)

 BMT - Fraud Wrongful or criminal deception intended to 

result in financial or personal gains including 

extortion, embezzlement, visa fraud, and 

arranged marriages 

 BMT - Legit References to ownership of legitimate 

businesses including autoshops, tattoo parlors, 

PediCab, etc

Predatory Behavior (PB) Defined by two subvariables: PBA and PBVB

PBA -Assassin/Enforcer

PBVB - Violent Behavior References to violent activities by individual 

or gang (carjackings, drive by shootings, 

assaults) and/or intra-group violence including 

verbal and physical violence. 

Linkage to Organized 

Crime (LOC)

Refers to (1) Mexican Mafia or Cartels (2) 

'circles' or 'closed rings', (3) organized crime or 

organizations (4) smuggling (5) residences 

involved in CSEP (6) collusion with law 

enforcement (7) organized 'slavery' or 

'trafficking'

Inter-Group Alliances 

(IGA)

Cooperation between individuals, gangs, and 

groups. Could be informal, loosely organized, 

or formal partnerships

Information & Notes General information of note regarding this 

interview

Military Weapon Source 

(MWS)

When military is reported as a source, 'Weapon 

Source' refers to the precise mechanism/

processes by which weapons are acquired

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154

Appendix C 

Gang Structure Analysis 

Version 10-Jul-2015 

Introduction 

Gang organization shows considerable variation and can best be seen on a continuum. At 

one extreme, gangs are described as highly organized groups, while at the other they are 

described as ineffective social mechanisms, which lack key features of organizational structure. 

The former may be thought of as instrumental-rational (organized) and the latter as informaldiffuse (disorganized) models of gang organization. These ideal types were developed during the 

debate over the extent to which gangs controlled the increasingly violent U.S. street-drug 

markets in the 1990s. Hagedorn contrasted organized drug distributors with "freelance" drug 

dealers, concluding that the latter was a description more consistent with the data.

Importantly, Morselli discovered that gang members participate in a number of different 

crimes and groups, in addition to those committed with their own gang. He notes that while some 

of their crimes are linked to their membership in the gang, others clearly are not. The research on 

gang organization has expanded beyond drug selling to areas such as the penetration of gangs 

into community organization and the ability of gangs to organize homicide. 

We used an analytical framework developed by Andrea Spindler and Martin Bouchard 

(2011) that combines structural and behavioral characteristics. (Other typologies use one or the 

other, but not both). The combined variables allow us to say where different groups fall on the 

continuum of instrumental-rational (organized) to informal-diffuse (disorganized). 

Defined in the Glossary of Terms, Gang Structure was operationalized using eight macrovariables: Rules, Size, Intergenerational, Complexity, Undirected Facilitation, Directed 

Facilitation, Behavioral Market Types, Predatory Behavior, and Linkages to Organized Crime. 

Three of these - Complexity, Behavioral Market Types, and Predatory Behavior - are broken 

down into sub-variables. The most highly organized gangs is defined as one that has rules, are 

large in size, are intergenerational, highly complex (meaning they are coded yes or 1 for all of 

the sub variables [except, perhaps, territoriality – see H4 below), engage in multiple markets, are 

predatory, and have linkages to organized crime. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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155

Hypotheses 

Four hypotheses guided this research: 

 H1: The majority of San Diego gangs fall towards the informal-diffuse end of the 

continuum

H1a: The majority of gang members in our data set describe belonging 

to informal-diffuse groups 

 H2: A minority of facilitation is directed as a market activity by highly organized gangs

H2a: A majority of facilitation is undirected by individual members of both 

organized and unorganized gangs 

 H3: Gangs with linkages to organized crimes are more likely to be engage in Predatory 

Behavior

H3a: Gangs with linkages to organized crime are more likely to be highly 

organized than gangs without linkages to organized crime 

 H4: Territorial gangs are more disorganized than non-territorial gangs

H4a: Non-territorial gangs engage in a higher number of illicit markets than 

territorial gangs 

Dataset Generation 

We began with a small dataset (N = 73) of viable interviews with gang members in San 

Diego County correctional facilities. We collapsed that dataset by primary gang affiliation, to 

create a smaller dataset (N = 50) in which gangs were the unit of analysis, all individuallyreported gang characteristics were averaged, and observations were summed to retain a sense of 

the size of representation for each gang. We also used stepwise elimination multiple imputation 

to generate predictions of missing values for those four variables (size, intergenerationality, 

oldest member, and duration) for which more than 10 missing values were observed. 

In order to generate a single variable denoting the latent variable “complexity,” we 

perform a Principal Components Analysis (PCA) on the 11 relevant variables (see Table and 

Figure 3). We then scale the first principal component such that the minimum and standard 

deviation is 1. The inclusion of the first principal component in our analysis is a useful way of 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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156

accounting for data from numerous variables in a regression model without losing too many 

degrees of freedom. Indeed, the first component in this case explains about 42.5% of the 

variation contained in all 11 variables. 

Table 2. Principal components (eigenvectors) 1-11 of the chosen complexity variables. 

D

escription 1 2 3 4 5 6 7 8 9

1

0

1

1

U

nexplain

ed

R

ules

0

.25

-

0.07

-

0.55

0

.16

-

0.38

0

.41

0

.07

-

0.01

-

0.02

0

.21

0

.50 0

Si

ze

0

.32

0

.00

-

0.03

-

0.67

0

.15

0

.51

0

.12

0

.18

0

.12

0

.05

-

0.31 0

Int

ergeneratio

nality

0

.32

-

0.05

0

.46

-

0.07

-

0.38

-

0.10

-

0.10

-

0.09

0

.66

-

0.12

0

.24 0

D

uration

0

.43

-

0.06

-

0.03

-

0.19

0

.12

-

0.07

-

0.41

-

0.36

-

0.42

-

0.49

0

.19 0

Te

rritoriality

0

.22

-

0.42

0

.38

0

.23

0

.19

0

.16

-

0.41

0

.26

-

0.20

0

.49

0

.04 0

In

dustry 

specializati

on

0

.40

-

0.06

-

0.26

0

.20

0

.00

-

0.33

0

.05

0

.71

0

.06

-

0.32

-

0.13 0

R

ole 

differentiati

on

0

.36

0

.29

-

0.23

-

0.07

-

0.21

-

0.41

-

0.18

-

0.26

0

.00

0

.52

-

0.38 0

Su

b-groups

0

.21

-

0.50

-

0.07

-

0.10

0

.36

-

0.34

0

.56

-

0.26

0

.07

0

.16

0

.18 0

Pr

omotions

0

.30

0

.17

0

.42

0

.23

-

0.33

0

.15

0

.53

-

0.05

-

0.45

-

0.06

-

0.17 0

Ta

x structure

0

.09

0

.60

0

.17

-

0.20

0

.31

-

0.16

0

.08

0

.25

-

0.10

0

.21

0

.56 0

Le

ader

0

.27

0

.29

-

0.06

0

.53

0

.52

0

.30

0

.01

-

0.25

0

.33

-

0.09

-

0.14 0

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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157

Figure 3. Scree plot of Eigenvalues following Principal Components Analysis of gang complexity. 

However, the PCA variable does not allow us to compare the complexity observed in the 

sample with the total complexity permitted by our relevant variables. Part of the problem is that 

there is no upper limit on such continuous variables as “duration of the gang” and “number of 

members.” Therefore, we also created a simple score of gang complexity that sums all nine 

relevant binary variables: rules, intergenerationality, control of territory, industrial specialization, 

role differentiation, sub-groups, promotion possibilities, tax structure, and leadership. We then 

normalized that score variable by the highest score possible (9). Unfortunately, such a score is 

only applicable to those gangs for which data on all nine variables was available, leaving us with 

just 20 observations. Whilst such a low number should make us cautious when interpreting or 

generalizing from such data, it notable that (as Figure 4 shows) represented San Diego gangs 

display a bimodal pattern of complexity: a few gangs are relatively simple, whilst the majority 

cluster at the medium-high end of the spectrum. 

0 1 2 3 4 5

Eigenvalues

0 5 10

Number

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Figure 4. Histogram of the normalized complexity sum score of gang complexity (range: 0-1)

Market Share Analysis and Arrest Under-/Over-Representation 

We seek in this section to get a sense of the gang market place: if gangs compete in 

similar illicit markets (and this is debatable), then we can calculate an index of market 

monopoly. The classic index is the Herfindahl-Hirschman Index, or HHI, which is calculated 

simply as 

HHI = ∑ si

2

N

i=1

where si

is the share size of gang-dominated markets captured by gang i and N is the 

total number of gangs. We also calculate the normalized HHI as defined by the equation 

HHIn =

HHI−1

N

1−1

N

,

which allows the HHI to range from 0 to 1, rather than from 1/N to 1. 

Furthermore, we calculate the HHI on two different bases. First, we take the number of 

arrested individuals as being representative of total gang size, such that si becomes the number 

of gang members representing each gang in our dataset divided by total gang members in our 

dataset. This is likely a problematic method, since it is not at all obvious that gangs engage in 

illegal activities or avoid police capture to roughly unvarying degrees. Second, we take the 

average estimates of respective gang size by the affiliated gang members, divided by the sum of 

those average estimates, to be si. This method may suffer from reporting bias (gang members 

wishing to over- or under-represent the importance of their gang), ignorance bias, and fact that 

0 2 4 6

Frequency

0 .2 .4 .6 .8

Normalized complexity sum score

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the aforementioned biases will tend to affect less-represented gangs more than better-represented 

gangs in the correctional system. 

Table 1 reports the calculations. The U.S. Department of Justice regards HHIs of 0.15-

0.25 to represent moderately concentrated markets, and HHIs of over 0.25 to be highly 

concentrated. The formulation 1/HHI roughly corresponds to the number of competitive firms in 

the marketplace. (Smith & Dunne, 2015) We see then that, if we define the market for gangdominated economic activity as being geographically bounded by San Diego County47, the 

market is quite competitive, with roughly 15 gangs sharing market dominance in the county, as 

judged by the normalized HHI for reported gang size. Indeed, from an economic perspective, the 

illicit sex industry is an inherently “labor-intensive” one, and therefore does not benefit greatly 

from economies of scale (as the drug trade might). In that sense, a lack of industry concentration 

is to be expected. 

Table 1. HHIs based on numbers of observations and reported gang size. 

Method base HHI

Normalized 

HHI

Observations 0.031 0.011

Reported 

gang size 0.066 0.065

The two different bases for the HHI calculations also yield a metric for determining 

which gangs are under-represented in the correctional system, and which are over-represented. 

To create our Under-Representation Index (URI), we normalize the market share variable (as 

calculated by average reported size) by the variable describing the share of total respondents 

represented by the gang in question. We then natural log transform the result in order to 

emphasize differences in values less than 1. Mathematically, we can write 

URIi = ln (

si

obsi

)

In this index, a value of 0 signifies that the number of gang members in prison is 

perfectly in proportion to its size. Values higher than 0 signify that the gang is underrepresented 

in the correctional system, whilst values below 0 signify the opposite. Figure 5 depicts a 

histogram of the URI. Indeed, the distribution seems for the most part to be normally distributed 

 

47 This assumption is problematic, as there is very likely geographic and economic market segmentation 

that allows certain gangs to have monopolies in certain activities or neighborhoods. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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160

around 0 – that is, around proportional representation. A small secondary concentration occurs 

around highly over-represented gangs. However, that concentration should be interpreted with 

caution, as two of the lowest-scoring entries were idiosyncratic: Krink had no listed size, and 

since the multiple imputation-predicted size was negative, it was automatically assigned the 

minimum size of the sample (which happened to be 10). The other entry was for a gang the 

respondent did not wish to name, so it is treated as unique, rather than potentially being grouped 

with another gang in the sample. Throwing these two out, the histogram looks fairly regularly 

distributed, though left-skewed (skewness = - -.18, kurtosis = 2.74). Table 2 lists the highly 

under- and over-represented gangs in the correctional system by name and score. 

Figure 5. Histogram of the URI. 

Table 2. Highly under- and over-represented gangs in the correctional system (URI > +2 or URI < -2).

Rank Name URI

Underrepresented1

Elements 2.06

2 Palms 2.37

Overrepresented1

Carnies -3.63

2 Irises -3.55

3 Creeks -3.12

4 Apples -2.72

5 Fortune 

Tellers -2.72

0 2 4 6 8

Frequency

-4 -2 0 2

Under-representation index (URI)

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161

6 Tremors -2.43

7 Sliders -2.21

Sex Facilitation and Gang Organizational Complexity 

We ran logit regressions for the pseudo-binary outcome of “directed facilitation” – that is, 

whether or not the gang directly organizes its members’ roles in the sex trade – against various 

variables concerning the complexity of the gang organizational structure.48 Interestingly, the first 

component of the complexity PCA is not significant, though that may be an artifact of extremely 

low sample size. Model 13 includes all individual variables, and Model 14 is a stepwise 

elimination version (at the P<0.20 level) of Model 13. 

According to the final model, the establishment of clear rules of conduct and the 

possibility for promotion within the gang are both positively and significantly associated with 

directed facilitation. It bears mentioning, of course, that these associations cannot be taken for 

causal relationships, and that causality may even run the other way.49 That is, being involved in 

directed sex facilitation may induce an organizational change toward greater institutional rule 

generation and the possibility for promotion. One narrative might be: It is well appreciated in the 

civil war literature that members of insurgent organizations financed in “bottom-up” fashion are 

less accountable to hierarchical superordinates than those financed in “top-down” fashion 

(Lidow, 2008). Similarly, gangs that rely on street-level facilitators to “kick up” a percentage of 

revenues to them face an information problem: they do not know what the total amount earned 

by each facilitator is. Therefore, they may choose to institute norms and rules that guard against 

 

48 Oftentimes, results obtained by OLS with binary outcomes do not differ greatly from those obtained via 

logistic/logit estimators for average marginal effects. However, the latter are considered superior when estimating 

probabilities (Pohlman & Letner, 2003) or handling skewed data (Beck, 2011), and our study does both. Our 

outcome, though, is not truly binary. Were we to rely only on one supposedly authoritative source, it could only take 

on two values. Our variable is “pseudo-binary” because we have averaged the responses from multiple respondents 

in the same gang – responses that mostly, but do not always, accord with one another. Many seemingly binary 

variables in this dataset (the directed facilitation variable included), while being populated by and large by 0s and 1s, 

are really bounded between 0 and 1 with a few decimal values bimodally lumped in proximity to one or the other 

extreme. There is nothing about the logistic estimator that would preclude modeling such an outcome, and indeed 

some evidence that it is appropriate as long as the original data (though now collapsed) originated with some form of 

Bernoulli experiment. 

4949 Cases in which causality may be bidirectional or common variation is attributable to a third, latent 

variable are endogenous and should be treated specially, for instance with simultaneous equations which include an 

instrumental variable that is both exogenous and relevant. Here, we have no such IV, as the data collected have not 

been subject to a randomized control trial of some intervention, nor experienced a natural experiment. 

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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.
162

the possibility of fraud, as well as incentive structures that promise future rewards for present 

loyalty. 

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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.
163

Table 3. Logit models fit for “directed facilitation” regressed on gang complexity variables

VARIABLES (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

First component: Complexity 0.684

(0.673)

Rules (Y/N) 0.664 29.39 2.790*

(0.766) (37.93) (1.605)

Size 3.41e-05 0.00534

(0.000324) (0.00706)

Intergenerationality 0.312 -1.531

(0.872) (4.778)

Duration 0.0306 -0.768

(0.0208) (1.024)

Complexity: Territorial (Y/N) 0.408 -6.350

(0.684) (10.81)

Complexity: Industry specialization 

(Y/N) 0.552 -2.938

(0.737) (6.553)

Complexity: Role differentiation

(Y/N) 2.663*** 1.475

(0.947) (6.299)

Complexity: Sub-groups (Y/N) -0.634 -4.895

(0.670) (6.587)

Complexity: Promotion (Y/N) 2.175** 24.52 4.153**

(0.911) (30.54) (1.712)

Complexity: Tax structure (Y/N) 1.755** -3.446

(0.772) (7.603)

Complexity: Leader (Y/N) 2.356*** -5.400 -1.961

(0.855) (5.146) (1.435)

Constant -0.636 0.223 0.776* 0.802 -0.201 0.693 0.343 -0.183 1.040** 0.162 -0.247 -0.189 7.045 -1.659

(1.925) (0.652) (0.417) (0.725) (0.763) (0.470) (0.627) (0.432) (0.472) (0.456) (0.513) (0.477) (11.84) (1.444)

Observations 14 46 42 38 40 45 47 44 46 41 42 44 28 28

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

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164

Territoriality and Organizational Complexity 

Territoriality was one of the 11 original variables we used to define the PCA variable for 

complexity of gang organizational structure. The variable was positively but weakly and 

insignificantly relatedly to the resulting first principal component. It was also one of the nine 

binary variable summed to get a complexity index. There is some tautology, therefore, in 

attempting to link these index outcomes with the original territoriality variable. Instead, we here 

look at the territoriality as an outcome of other putative indicators of organizational complexity 

(see Table 4).

Of all 10 possible predictors introduced, only rule imposition and the formation of subgroups are positively and significantly associated with territoriality in bivariate regressions. It 

might be hypothesized that gangs that stay in one place are more reliant on the communities in 

which they find themselves for support. This accords with the idea that “stationary bandits” must 

behave in less predatory fashions than “roving bandits,” who do not come into iterative contact 

with the same parties, and so do not have the same incentives to build trust (Olson, 1993). 

Akerlof and Yellen (1993), too, reason that territorial gangs have a primary interest in cultivating 

relationships with (but also be able to make credible treats against) locals in order to prevent 

them from leaking information on their illicit activities to police and other official authorities. 

Rules about when the carrot is offered or the stick brought out might be key elements of longterm strategy for local involvement. This line of reasoning fits with the idea that non-state groups 

that have a competitive advantage in social (rather than economic) endowments will invest more 

in expensive disciplinary structures in order to restrain the violent excesses of their members and 

preserve their social support (Weinstein, 2002, 2007).

Interestingly, neither of these variables remains significant in the multivariate and 

stepwise multivariate models (11 and 12, respectively). Rather, duration and promotion 

possibilities are positively associated with territoriality, whilst group size and role differentiation 

are negatively related. These may simply be tautologous attributes of territoriality, however: for 

instance, non- or trans-territorial gangs may naturally have more members than those that have 

not “scaled up”. Likewise, gangs that have lasted longer will have had more time to grow out of 

initial territories. And if a group operates in many locations, they may be exploiting economies 

of scale and specialize in one line of work – hence the lack of role differentiation and promotion 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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165

possibilities. However, as with all the multivariate models, it is important to note that the number 

of useable observations falls dramatically, and that the small sample size may introduce 

problems of representativeness, in addition to the obvious issue of statistical power. With such a 

low n, a model should probably not contain more than two predictors.50

 

50

 If we use the rule of thumb that n = k(m + 1) where m is the number of predictors and k is a constant 

whose lowest “acceptable” value is 10.

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166

Table 4. Logit models of territoriality regressed on other putative indicators of organizational complexity. 

VARIABLES (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

Rules (Y/N) 1.378* -0.241

(0.802) (3.431)

Number of members -0.000200 -0.00228* -0.00219**

(0.000301) (0.00134) (0.00105)

Intergenerational (Y/N) 1.144 0.940

(0.849) (3.110)

Duration 0.0191 0.153 0.151**

(0.0188) (0.104) (0.0751)

Complexity: Industry specialization 

(Y/N) 0.948 0.994

(0.764) (2.396)

Complexity: Role differentiation 

(Y/N) 0.603 -3.193 -3.011*

(0.682) (3.985) (1.639)

Complexity: Sub-groups (Y/N) 1.152* 0.962

(0.654) (1.321)

Complexity: Promotion (Y/N) 1.028 1.740 2.477**

(0.680) (2.946) (1.260)

Complexity: Tax structure (Y/N) 0.353 0.757

(0.680) (3.841)

Complexity: Leader (Y/N) 0.775 -0.320

(0.685) (1.763)

Constant -0.837 0.610 -0.513 -0.388 -0.454 0.0982 -0.285 -0.454 -0.00801 -0.0823 -3.560 -1.993

(0.700) (0.407) (0.732) (0.746) (0.665) (0.448) (0.429) (0.489) (0.492) (0.499) (4.201) (1.430)

Observations 45 41 39 40 44 42 46 40 42 44 28 28

Pseudo-R2 0.0517 0.00808 0.0356 0.0196 0.0264 0.0140 0.0514 0.0427 0.00468 0.0218 0.355 0.311

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

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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.
167

Predatory Behavior and Organizational Complexity 

Our dataset contains binary variables on whether the gang engages regularly in 

assassinations and violence. Herein, we ask to what extent these outcomes are related to 

organizational complexity and structure. Logit results for assassinations are reported in Table 5

and are universally insignificant, save for a hint in the multivariate model that old gangs tend to 

engage in assassinations less than young ones. This finding must be conditioned by the 

aforementioned caveat about the small-n multivariate models. 

Bivariate models predicting violence employment generate positive and significant 

associations for territoriality, duration, role differentiation, promotion, and tax structure (the 

latter of which continues to be significant in the stepwise-elimination multivariate model). Many 

of these might have straightforward explanations. For instance, groups that impose “taxes” on 

their communities or their employees’ own revenue generating activities will likely have to back 

up the demand with the threat of violence upon non-compliance. Likewise, gangs that seek to 

establish and maintain territory may compete with other gangs directly or via local support (or, 

conversely, the denial of local support to rivals), both of which may require the employment of 

violence. The employment of violence in gangs that exhibit role differentiation and promotion 

opportunities – in other words, hierarchical organizations – may simply be a necessary part of 

maintaining discipline when revenues are generated in “bottom-up” fashion.

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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168

Table 5. Logit models of assassinations regressed on other putative indicators of organizational complexity. 

VARIABLES (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Rules (Y/N) = o, - -

Number of 

members -5.57e-06 0.00458

(0.000426) (0.00297)

Intergenerational 

(Y/N) -0.379 -16.64

(1.217) (13.65)

Complexity: 

Territorial (Y/N) -0.00543 2.252

(0.989) (2.723)

Duration 0.00866 -0.144*

(0.0271) (0.0833)

Complexity: 

Industry 

specialization 

(Y/N) 0.582 -0.714

(1.197) (4.616)

Complexity: 

Role 

differentiation 

(Y/N) 0.704 -14.47

(1.167) (14.61)

Complexity: 

Sub-groups 

(Y/N) -1.108 0.887

(1.122) (2.584)

Complexity: 

Promotion (Y/N) 0.654 16.65

(0.969) (12.40)

Complexity: Tax 

structure (Y/N) 0.733 12.95

(1.172) (14.68)

Complexity: 

Leader (Y/N) 0.851 -3.500

(1.174) (4.949)

Constant -1.504*** -1.815*** -1.895* -2.076*** -2.300** -2.332** -2.639*** -1.687*** -2.124*** -2.491** -2.613*** 0.910 -1.386**

(0.451) (0.548) (0.998) (0.722) (1.151) (1.080) (0.888) (0.577) (0.769) (0.970) (0.970) (2.234) (0.559)

Observations 33 43 39 45 41 45 42 46 40 42 44 20 20

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

VARIABLES (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

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169

Table 6. Logit models of violence employment regressed on other putative indicators of organizational complexity. 

Rules (Y/N) 1.209 3.293 3.443*

(0.773) (3.838) (1.983)

Number of members 0.000477 -3.66e-05

(0.000442) (0.00118)

Intergenerational (Y/N) 0.748 1.114

(0.834) (2.822)

Complexity: Territorial (Y/N) 1.191* 1.576 1.817

(0.700) (2.150) (1.373)

Duration 0.0357* 0.00107

(0.0210) (0.0738)

Complexity: Industry specialization (Y/N) 0.822 0.453

(0.734) (2.331)

Complexity: Role differentiation (Y/N) 2.045** 0.0772

(0.866) (3.563)

Complexity: Sub-groups (Y/N) 0.323 -0.204

(0.671) (1.881)

Complexity: Promotion (Y/N) 1.232* -0.0636

(0.746) (2.354)

Complexity: Tax structure (Y/N) 1.752** 4.196 4.239**

(0.760) (3.917) (1.895)

Complexity: Leader (Y/N) 0.782 -2.729 -2.382

(0.733) (2.279) (1.807)

Constant -0.207 0.480 0.362 0.176 -0.490 0.146 0.107 0.542 0.186 -0.367 0.441 -4.325 -3.771*

(0.651) (0.423) (0.683) (0.457) (0.767) (0.620) (0.430) (0.441) (0.455) (0.517) (0.484) (3.956) (2.217)

Observations 45 42 38 44 40 47 44 45 40 42 43 28 28

Pseudo-R2 0.0431 0.0291 0.0173 0.0550 0.0643 0.0211 0.128 0.004 0.0577 0.105 0.0219 0.319 0.291

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

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170

Links to Organized Criminal Groups 

When run in bi- and multivariate regressions on our organizational complexity and 

structure variables, there are no statistically significant associations whatsoever with the outcome 

of linkages to organized crime. It seems that groups of all shapes and sizes are linked 

indiscriminately to organized criminal groups. Likewise, when we use links to organized 

criminal groups as a predictor for predatory behavior (assassinations and violence), we find no 

significant correlations. For that reason, we do not present these results. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

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1 

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Spinderl, Andrea and Martin Bouchard (2011). Structure or Behavior? Revisiting Gang 

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University Press. 

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.