Highlights
• There are clear and recognised benefits to geographical perspectives on human trafficking.

• Yet, quantitative geospatial analysis is especially rare, partly due to data access issues.

• Identified victims’ case files contain extensive but largely unstructured geographical data.

• Focusing on labour trafficking (n = 450), we find five key methodological challenges for analysis.

• They are 1) data integrity; 2) geographical uncertainty; 3) complex geographies; 4) diversity & disaggregation; 5) unclear journeys.

Abstract

There is relatively little empirical research into the geographies of human trafficking, despite its inherent spatiality and the clear benefits of geographical perspectives. An emerging but vibrant body of qualitative work explores different aspects of trafficking’s spatiality and spatio-temporality in depth and nuance, but equivalent quantitative analyses are notably lacking. What exists is largely limited to crude maps and broad-brushed assessments of patterns and trends. Yet, rigorous quantitative work is also vital in advancing understanding, informing responses and increasing accountability. In this paper, we present a novel, empirically-substantiated examination of methodological challenges in mapping trafficking. We draw on analysis of data extracted from the case files of 450 formally identified labour trafficking victims (accessed via the UK’s National Crime Agency). We identify and illustrate five characteristics of the data creating particular challenges for geospatial analysis: data integrity (regarding completeness, accuracy and consistency); geographical uncertainty (regarding spatial accuracy and specificity); managing multiple geographies (trafficking is a complex process with various stages, each potentially involving numerous locations); diversity and disaggregation (important geographical variations can be masked in aggregated analysis); and unclear journeys (analysing trafficking routes proved particularly complicated). We also consider possible solutions and explore implications for future research, policy and practice.

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