Kiss, L;
Fotheringhame, D;
Mak, J;
McAlpine, A;
Zimmerman, C;
(2020)
The use of Bayesian networks for realist evaluation of complex interventions: evidence for prevention of human trafficking.
Journal of Computational Social Science
10.1007/s42001-020-00067-8.
(In press).
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Abstract
Complex systems and realist evaluation ofer 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 efects. 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-trafcking intervention by the International Labour Organisation in South Asia. We used BN to explore causal pathways to human trafcking using data from 519 Nepalese returnee migrants. The fndings suggest that risks of trafcking are mostly determined by migrants’ destination country, how they are recruited and in which sector they work. These fndings challenge widely held assumptions about individual-level vulnerability and emphasize that future investments will beneft from approaches that recognise the complexity of an intervention’s causal mechanisms in social contexts. BNs are a useful approach for the conceptualisation, design and evaluation of complex social interventions.
| Type: | Article |
|---|---|
| Title: | The use of Bayesian networks for realist evaluation of complex interventions: evidence for prevention of human trafficking |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s42001-020-00067-8 |
| Publisher version: | http://dx.doi.org/10.1007/s42001-020-00067-8 |
| Language: | English |
| Additional information: | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Complex systems, Realist evaluation, Bayesian network, Human trafcking, Forced labour, Nepal |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10109300 |
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