The lack of knowledge on the magnitude of the human-trafficking problem regionally and internationally remains the weakest link in the current countertrafficking movement and has given rise to estimates and unsubstantiated claims; however, difficult-to-count populations such as trafficking victims pose significant sampling challenges for social scientists because a sampling frame cannot be reliably established. As a result, field researchers often choose to accept nonparametric strategies such as convenience sampling at the cost of weakened generalizability and inferential potential. The pilot study included 543 dwellings randomly drawn from U.S. Census block and block clusters in four North Carolina counties. Findings support the rationale behind the field enumeration strategies and its cost effectiveness in establishing a sound sampling frame for our target population. The study concludes that this sampling strategy may offer considerable value for future fieldwork among the difficult-to-count migrant farmworker population. (publisher abstract modified)
Estimating Labor Trafficking Among Farmworkers: An Inverse Sampling Strategy Based on Reliable Housing Predictions
NCJ Number
252569
Journal
Journal of Human Trafficking Volume: 1 Issue: 2 Dated: July 2015 Pages: 117-165
Date Published
July 2015
Length
19 pages
Annotation
This article reports on a pilot study in 2013 to test whether a new sampling frame enumeration strategy, based on Global Positioning System (GPS)-enabled field inspections, would be economically feasible and methodologically reliable for estimating labor trafficking among farmworkers.
Abstract