Forum on Crime and Society
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Forum on Crime and Society

Special Issue - Researching Hidden Populations: Approaches to and Methodologies for Generating Data on Trafficking in Persons

This issue of the United Nations Office on Drugs and Crime journal Forum on Crime and Society focuses on research related to trafficking in persons. It contains articles by a range of researchers and academics with experience in identifying 'hidden populations' such as trafficking victims. The articles present research methods and approaches that have been used with success to uncover 'hidden populations' in different contexts in the past. It is hoped that this edition of the Forum will stimulate the generation of more sound data on the different aspects of trafficking in persons worldwide.
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Proposed utilization of the network scale-up method to estimate the prevalence of trafficked persons You do not have access to this content

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Author(s):
Janie F. Shelton

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Trafficking in persons is one of the gravest of crimes, but the scope and extent of the crime as measured by the number of victims have scarcely been quantified. Generating data on the population of trafficked persons presents a unique challenge because it tends to be a very hidden population—much more hidden than other hidden populations, such as the homeless population or the drug-injecting population. Epidemiological methods to detect hidden populations have advanced in recent years, with a variety of research papers describing the use of the network scale-up method to detect key affected and other subpopulations. The approach relies on conducting a survey of the general population, in which questions are asked about the number of individuals of interest in the personal network of the respondent and a specific set of questions are devised to estimate the size of the respondent’s network. Advantages include the detection of multiple populations of trafficked persons in one survey, the minimization of harm to respondents for divulging first-hand knowledge, and improved statistical accuracy achieved by averaging over a large sample. Disadvantages include limited knowledge of the covariates of the population being surveyed.