DOI: 10.3886/icpsr36220
title: The Nature and Extent of Gang Involvement in Sex Trafficking in San Diego County, California, 2003-2015
title: Archival Version

description: This three-year study used quantitative and qualitative data collected between 2003 and 2015 to assess the scale and nature of gang involvement in sex trafficking in San Diego, California. At the time of study, San Diego was ranked as one of the United States' highest areas of commercial sexual exploitation of children (CSEC). This mixed-methods study has generated the following datasets:

Survivor Services Dataset (DS1 and DS2): A composite of intake surveys conducted by the prostitution diversion program Freedom From Exploitation (FFE) (DS1) and eight organizations that provide direct services to sex trafficking victims/survivors (DS2)
Law Enforcement Reporting Dataset (DS3 and DS4): Booking records provided by the San Diego Sheriff's Department (DS3), and arrest records provided by the Automated Regional Justice Information System (ARJIS) (DS4)
Schools Dataset (DS5): Summaries of focus group interviews of staff employed by San Diego County school districts (due to disclosure concerns, full transcripts were not released)
Facilitator Interview Dataset (DS6): Summaries of interviews of incarcerated and community members with knowledge of trafficking (due to disclosure concerns, full transcripts were not released)
Social Media Analytics Dataset (DS7): Search criteria and schema of relevant data fields for social network analysis conducted using Twitter data (due to disclosure concerns and dataset size, the social media data themselves were not released)
Survivor services, law enforcement, schools, and facilitator interview data were all collected and analyzed as part of the main NIJ award. The social media analytics data were collected and analyzed under a subaward by the SecDev Cyber Group.
description: The purpose of the main study is to investigate the nature and assess the scope of gang involvement in sex trafficking and commercial sex activity in San Diego County, including detailed analysis of sex trafficking facilitation, as well as the scope of victimization and estimates of the regional commercial sex economy.
The purpose of the social media analysis is to investigate the digital ecosystem linking gangs operating in San Diego, Tijuana, and other parts of Latin America. Relative to the main study's purpose, the team focused on mapping online gang involvement in sex trafficking in San Diego and Tijuana, but the project also generated a methodology for social media-based terrain studies to understand the distribution and dynamics of online gang networks at micro- and macro-level scales.
description: <strong>Survivor services dataset.</strong> The research team analyzed existing survey data from Freedom From Exploitation (FFE), a diversion program offered to all individuals arrested for their first offense of prostitution. Survey data were collected for research purposes since 2005 (with permission from clients) during mandatory intake meetings. Items from the modified Trafficking Victim Identification Tool (TVIT) were also incorporated for the duration of the study for comparison purposes and to include questions about gang involvement. Eight nonprofit organizations that offer direct services to trafficking victims agreed to pilot the TVIT during their intake processes and provided intake data to the research team. For analysis purposes, TVIT items for the vast majority of intake and survey forms were coded retrospectively.
<strong>Law enforcement reporting dataset.</strong> Law enforcement data were used to estimate the number of arrests in which at least one victim of commercial sexual exploitation could be identified. The San Diego Sheriff's Department provided records of bookings into county jails regardless of arresting agency between 2003-2014. Arrest data between January 2007 and June 2014 were provided by the Automated Regional Justice Information System (ARJIS), a joint powers agency created to share information among justice agencies throughout San Diego and Imperial Counties, California.
<strong>Schools dataset.</strong> In order to learn about incidents of recruitment/engagement in commercial sexual exploitation and gang activity within high school settings, the research team conducted focus groups with staff across 20 high schools in 4 school districts in San Diego County. After gaining permission from district personnel, district administration made principals aware of the project and requested participation. Each focus group had an average of 7 individuals.
<strong>Facilitator interview dataset.</strong> Researchers conducted interviews with individuals who were involved in or knowledgeable about trafficking. The vast majority of this sample were individuals held in protective custody in one of three San Diego detention facilities. All inmates in protective custody who wished to participate were eligible. Deputies made an announcement in each cell asking if inmates were interested in participating in a university research study. Those who were interested added their names to an opt-in list, and participants were randomly selected from the list and brought into a private room the day of the interview. As an incentive, incarcerated individuals received $10 in commissary credit upon interview completion, and community members received the same amount as a gift card.
<strong>Social media analytics.</strong> A subaward was granted to the SecDev Group to map online gang involvement in sex trafficking in and between San Diego, California and Tijuana, Mexico. Twitter was used as the primary platform for investigation due to its public accessibility. The team adopted an iterative, repetitive approach for continuous refinement of key indicators, which consisted of six stages:

Open source research to understand the target groups, geographical scope, and specific activities being explored (including building a gang slang lexicon), collecting all worldwide data against key indicators and all geotagged content within the specified geographical parameters, and dataset compilation
Building dashboards for visualization and interpretation of collected data, including cleaning and refining indicators
Deep-level analysis of profile content detected during data collection by social media scanners
Social network analysis and snowballing of detected and identified networks
Deeper analysis of social network analysis dashboards and profile content, including searching individual key indicators (geo-references, references to specific activities)
Mapping out network behaviors, relationships, motivations, nodes, and transnational connections
description: <strong>Survivor services dataset.</strong> Freedom From Exploitation (FFE) surveys include items designed to determine if the respondent is a victim of human or sex trafficking (e.g., ever had sexual contact without really wanting to), evaluate mental health, ask respondents' views on advantages and disadvantages of sexual exploitation/prostitution/survival sex, and gauge respondents' needs for assistance. Both datasets contain items from the Trafficking Victims Identification Tool (TVIT) on the respondent's migration to the U.S., living and working conditions, personal background, and any gang involvement in the respondent's circumstances. For both datasets, demographic variables include age, sex/gender, and race/ethnicity.
<strong>Law enforcement reporting dataset.</strong> Booking and arrest data contain location of arrest, date, penal code violated, and description of violation.
<strong>Schools dataset.</strong> Focus group participants were asked about their perceptions of and experience with recruitment and victimization related to sex trafficking at their schools, as well as the extent of gang involvement in trafficking activities.
<strong>Facilitator interview dataset.</strong> Participants were asked about their experiences with facilitating trafficking. Specifically, they provided perspectives on the average prostitute (age range and age limits), pimp (age range, what constitutes a "successful" pimp), and purchaser (age range). They also provided information on gang structure, membership, funding acquisition, and involvement in trafficking.
<strong>Social media analytics.</strong> Search keywords used included gang slang terms, gang names, geographic locations, and terms related to trafficking/prostitution.
description: Not applicable.
description: Response Rates: Not available.
description: Presence of Common Scales: Trafficking Victim Identification Tool (TVIT)
description: <strong>Survivor services dataset.</strong> Intake data from Freedom From Exploitation (FFE) includes all individuals who were referred to the diversion program between 2005 and 2015. Intake data from additional nonprofit organizations included all individuals referred to them who had a currently active case between June 2013 and June 2015.
<strong>Law enforcement reporting dataset.</strong> As the aim was to identify arrests in which at least one victim of commercial sexual exploitation could be identified, the research team originally sought to combine prostitution arrests with arrests for all penal codes related to human trafficking and false imprisonment. However, several codes were dropped from analysis as the actual cases they represented were unrelated to sex trafficking.
<strong>Schools dataset.</strong> 141 staff members, including administration, teachers, counselors, social workers, nurses, safety personnel, and other program staff, were interviewed. For recruitment, schools were sampled from North County, Central County, East County, and the South Bay. The team prioritized schools that registered high on self-reported gang involvement by students on the California Healthy Kids Survey. Schools represented the full range of socioeconomic diversity in their populations and geographies.
<strong>Facilitator interview dataset.</strong> 139 incarcerated individuals (124 male, 15 female) across three detention facilities, as well as 15 individuals in the community, were interviewed by the research team. Current/former facilitators who were not incarcerated were recruited via snowball sampling, relying on connections from former gang members still connected to the streets, other intermediaries who had relationships with current or former gang members, and referrals from study participants.
description: Datasets: 
DS0: Study-Level Files
DS1: Survivor Services Dataset: Freedom From Exploitation Survey Data
DS2: Survivor Services Dataset: Nonprofit Intake Data
DS3: Law Enforcement Reporting Dataset: Booking Data
DS4: Law Enforcement Reporting Dataset: ARJIS Arrest Data
DS5: Schools Dataset
DS6: Facilitator Interview Dataset
DS7: Social Media Analytics Dataset
description: Participants in a prostitution first offender diversion program
Sex trafficking survivors who sought services from a nonprofit that provided direct services to human trafficking victims
Arrests and bookings in San Diego County during the study timeframe
Staff working at high schools in San Diego County
Incarcerated individuals in protective custody and community members who had direct knowledge of trafficking
Twitter posts/profiles matching gang-related terms, geolocation tagging to San Diego, California and/or Tijuana, Mexico, and other query parameters determined by the research team
. Smallest Geographic Unit: Street address
description: record abstracts; face-to-face interview; web scraping; on-site questionnaireThe current study used an abbreviated version of the Trafficking Victim Identification Tool (TVIT) developed by the Vera Institute of Justice that consisted only of Section 2 (Personal Background), Section 3 (Migration), and Section 5 (Living and/or Working Conditions). The tool was also modified to include questions about gang involvement. Items from the TVIT were part of data collection for the Survivor Services Data (DS1 and DS2). For more information on TVIT development and the full questionnaire, please refer to this related publication from the Vera Institute of Justice.The terms "survivor" and "victim" are both used to refer to individuals who have been involved in human or sex trafficking throughout the metadata and study materials.