Human Trafficking: Policy Intervention

Author:

Mordeson John N.1,Mallenby Michel1,Mathew Sunil2,Acharjee Santanu3

Affiliation:

1. Department of Mathematics, Creighton University, Omaha, Nebraska 68178, USA

2. Department of Mathematics, National Institute of Technology, Calicut, 673601, Kerala, India

3. Economics and Computational Rationality Group, Department of Mathematics, Debraj Roy College Golaghat 785621, Assam, India

Abstract

In E. Lutz and R. Lotspich, sex markets and human trafficking: Cause–effect and policy interventions, The Protection Project Journal of Human Rights and Civil Society 2 (2009) 199–124, causal linkages between commercial sex and human trafficking were examined. A three-link chain of necessary conditions exists. All three are required for trafficking into commercial sex. Consequently, trafficking can be addressed by policy intervention at any link. Prospects for policy success at the three points of intervention were compared. It was shown that a strategy of suppressing sex markets is least likely to be successful in reducing the associated human trafficking. In this paper, we create a mathematical model of the work developed above. We use five methods to derive five different linear equations to measure the success of policy intervention. The methods are the analytical hierarchy process, the Guiasu method, the Dempster rule of combination method, the Yen method, and the set-valued statistical method. The equations are based on an expert’s opinion of the relative importance of the factors involved in sex trafficking. These equations are used to determine a measure of how well a particular state in the USA is doing in policy intervention.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Computer Science Applications,Human-Computer Interaction

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Operations research and analytics to combat human trafficking: A systematic review of academic literature;PLOS ONE;2022-08-29

2. A Review of Various Machine Learning Techniques for Brain Tumor Detection from MRI Images;Current Medical Imaging Formerly Current Medical Imaging Reviews;2020-10-18

3. Human Trafficking: Policy Intervention;Fuzzy Graph Theory with Applications to Human Trafficking;2018

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