Showing papers by "Bernard W. Silverman published in 2019"

Globalization and Modern Slavery

Abstract: This article presents a cross-national comparative analysis of the relationship between different dimensions of globalization and modern slavery. It argues that both the economic and political dimensions of globalization are strongly associated with lower levels of slavery prevalence. Recent estimates suggest there are more than 40 million people in some form of slavery and the United Nations has committed the world to ending this problem by 2030. Some argue that a race to the bottom, and the structure of economic incentives associated with globalization have contributed to the problem of modern slavery. Others argue that increased openness and the diffusion of values, the spread of democratic forms of rule, and the advance of human rights that come with globalization limit modern slavery. This article presents a preliminary empirical analysis of these arguments using data on slavery prevalence across more than 60 countries and various measures of economic and political globalization. The analysis shows that economic measures of globalization and higher levels of democracy are significantly related to lower levels of slavery prevalence, even after controlling for armed conflict and regional differentiation. In order to support these findings, the article examines the international law on slavery, definitions and conceptions of modern slavery, and comparative data on slavery prevalence modeled across indicators of economic and political globalization. It concludes with a discussion of the implications of these findings for the trade-offs between globalization and modern slavery.

Model fitting in Multiple Systems Analysis for the quantification of Modern Slavery: Classical and Bayesian approaches

Abstract: Multiple systems estimation is a key approach for quantifying hidden populations such as the number of victims of modern slavery. The UK Government published an estimate of 10,000 to 13,000 victims, constructed by the present author, as part of the strategy leading to the Modern Slavery Act 2015. This estimate was obtained by a stepwise multiple systems method based on six lists. Further investigation shows that a small proportion of the possible models give rather different answers, and that other model fitting approaches may choose one of these. Three data sets collected in the field of modern slavery, together with a data set about the death toll in the Kosovo conflict, are used to investigate the stability and robustness of various multiple systems estimate methods. The crucial aspect is the way that interactions between lists are modelled, because these can substantially affect the results. Model selection and Bayesian approaches are considered in detail, in particular to assess their stability and robustness when applied to real modern slavery data. A new Markov Chain Monte Carlo Bayesian approach is developed; overall, this gives robust and stable results at least for the examples considered. The software and datasets are freely and publicly available to facilitate wider implementation and further research.

Multiple Systems Estimation for Sparse Capture Data: Inferential Challenges when there are Non-Overlapping Lists

Abstract: Multiple systems estimation strategies have recently been applied to quantify hard-to-reach populations, particularly when estimating the number of victims of human trafficking and modern slavery. In such contexts, it is not uncommon to see sparse or even no overlap between some of the lists on which the estimates are based. These create difficulties in model fitting and selection, and we develop inference procedures to address these challenges. The approach is based on Poisson log-linear regression modeling. Issues investigated in detail include taking proper account of data sparsity in the estimation procedure, as well as the existence and identifiability of maximum likelihood estimates. A stepwise method for choosing the most suitable parameters is developed, together with a bootstrap approach to finding confidence intervals for the total population size. We apply the strategy to two empirical data sets of trafficking in US regions, and find that the approach results in stable, reasonable estimates. An accompanying R software implementation has been made publicly available.

Modelling Modern Slavery Risk

Abstract: The report was undertaken by Delta 8.7 - The Alliance 8.7 Knowledge Platform, a project of the Centre for Policy Research at United Nations University. Delta 8.7 symposia offer experts the opportunity to discuss technical details of their research and receive commentary from the wider research and anti-slavery community. In this Symposium on Modelling Modern Slavery Risk, Pablo Diego-Rosell (Gallup), and Jacqueline Joudo-Larsen (Walk Free Foundation) discuss their innovative methodology for modelling the risk of modern slavery, while four other data science experts—Laura Gauer Bermudez and Shannon Stewart from the Global Fund to End Modern Slavery, Bernard Silverman from the University of Nottingham and Kelly Gleason from Delta 8.7—discuss the benefits and limitations of their approach. Diego-Rosell and Joudo Larsen were then given the opportunity to respond to all of the interventions.