Complex systems and realist evaluation offer promising approaches for evaluating social interventions. These approaches take into account the complex interplay among factors to produce outcomes, instead of attempting to isolate single causes of observed effects. This paper explores the use of Bayesian networks (BNs) in realist evaluation of interventions to prevent complex social problems. It draws on the example of the theory-based evaluation of the Work in Freedom Programme (WIF), a large UK-funded anti-trafficking intervention by the International Labour Organization in South Asia. We used BN to explore causal pathways to human trafficking using data from 519 Nepalese returnee migrants. The findings suggest that risks of trafficking are mostly determined by migrants’ destination country, how they are recruited and in which sector they work. These findings challenge widely held assumptions about individual-level vulnerability and emphasize that future investments will benefit from approaches that recognize the complexity of an intervention’s causal mechanisms in social contexts. BNs are a useful approach for the conceptualization, design and evaluation of complex social interventions

The Use of Bayesian Networks for Realist Evaluation of Complex Interventions: Evidence for Prevention of Human Trafficking - Journal of Computational Social Science, 2019 DOWNLOAD














What is ‘Worker Voice’ in the context of global supply chains?

This brief provides a reference for worker reporting and worker empowerment tools and programs from the context of ‘worker voice,’ a concept that emerged with the birth of the organized labour movement during the Industrial Revolution. Two funda...Read More

Migrant Workers at Risk: Trends in Gulf Construction 2018−2019

An overview of the risks to migrant workers on construction projects across the Gulf. Migrant workers make up between 60% and 90% of the workforce in the six countries of the Gulf Cooperation Council (GCC). Low-wage construction workers are at parti...Read More

Technical Note: COVID-19 and Child Labour
COVID-19 resourcesGuidance

The United Nations declared 2021 the International year for the Elimination of Child Labour, an effort to eradicate this form of abuse and exploitation, a milestone in reaching the Sustainable Development Goal target 8.7. Worldwide, an estimated 152...Read More

TAGS: Global
Counter-trafficking Regional and Global Statistics at a glance
GuidanceStandards & Codes of ConductGood PracticesGraphics & Infographics

This report provides statistics and minor analysis regarding the demographics of those trafficked in 2015.

TAGS: Global