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Are Human Rights Practices Improving?

Published online by Cambridge University Press:  13 June 2018

DAVID CINGRANELLI  and
MIKHAIL FILIPPOV
DAVID CINGRANELLI*
Affiliation:
Binghamton University
MIKHAIL FILIPPOV*
Affiliation:
Binghamton University
*
David Cingranelli is a Professor of Political Science, Binghamton University, State University of New York, Vestal Parkway East, Binghamton, NY 13902-6000, USA (davidc@binghamton.edu).
Mikhail Filippov is an Associate Professor of Political Science, Binghamton University, State University of New York, Vestal Parkway East, Binghamton, NY 13902-6000, USA (Mikhail.filippov@gmail.com).
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Abstract

Has government protection of human rights improved? The answer to this and many other research questions is strongly affected by the assumptions we make and the modeling strategy we choose as the basis for creating human rights country scores. Fariss (2014) introduced a statistical model that produced latent scores showing an improving trend in human rights. Consistent with his stringent assumptions, his statistical model heavily weighted rare incidents of mass killings such as genocide, while discounting indicators of lesser and more common violations such as torture and political imprisonment. We replicated his analysis, replacing the actual values of all indicators of lesser human rights violations with randomly generated data, and obtained an identical improving trend. However, when we replicated the analysis, relaxing his assumptions by allowing all indicators to potentially have a similar effect on the latent scores, we find no human rights improvement.

Type
Letter
Information
American Political Science Review , Volume 112 , Issue 4 , November 2018 , pp. 1083 - 1089
Copyright
Copyright © American Political Science Association 2018 

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Footnotes

The authors thank Rodwan Abouharb, Sabine Carey, David Davis, Peter Haschke, Neil Mitchell, and David Richards for their helpful comments on earlier versions of this paper. Replication files are available at the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/KGVBNC.

References

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