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Estimating Labor Trafficking Among Farmworkers: An Inverse Sampling Strategy Based on Reliable Housing Predictions

NCJ Number
252569
Date Published
July 2015
Length
19 pages
Author(s)
Wayne J. Pitts; Kelle Barrick; Sheldon X. Zhang; Pamela K. Lattimore
Agencies
NIJ-Sponsored
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
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)

Date Created: July 20, 2021