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Are Online Opt-In Panels Viable Data Sources on Hard-to-Reach Populations? Population and Relational Inferences on Gang Membership in the United States

Author

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  • Pyrooz, David

    (University of Colorado Boulder)

  • Densley, James
  • Sanchez, Jose

Abstract

Criminologists maintain a vested interest in hard-to-reach populations, such as active offenders, former prisoners, and affiliates of criminal enterprises. For five decades, policymakers and researchers have sought national estimates of gang activity. Traditional methods, such as surveys sampling law enforcement agencies or youth populations, have provided valuable insights into gang activity in the United States. However, these approaches face limitations, including bias, obsolescence, high costs, outdated data, and restricted scope. This study examines the potential of online opt-in panels to studying gang populations. Contracting with YouGov, we administered four surveys to 13,148 respondents between January 2023 and January 2024, measuring lifetime gang membership and its correlates. Lifetime gang membership estimates ranged from 2.0% to 2.4% in custom surveys and 5.3% to 6.2% in omnibus surveys. While demographic and socioeconomic correlates showed mixed results, ecological and legal correlates consistently aligned with expectations based on prior research. Our findings suggest cautious optimism about the utility of online opt-in panels for studying hard-to-reach populations like gang members and advancing cross-national, comparative research in line with the Eurogang Program of Research. These panels offer advantages such as cost-efficiency, accessibility, and timeliness, but further validation is necessary to establish their reliability and validity for population-level estimates.

Suggested Citation

  • Pyrooz, David & Densley, James & Sanchez, Jose, 2024. "Are Online Opt-In Panels Viable Data Sources on Hard-to-Reach Populations? Population and Relational Inferences on Gang Membership in the United States," SocArXiv ser2g, Center for Open Science.
  • Handle: RePEc:osf:socarx:ser2g
    DOI: 10.31219/osf.io/ser2g
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