Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-22T10:51:17.788Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic Patterns of Human Rights Practices*

Published online by Cambridge University Press:  08 October 2013

Keith E. Schnakenberg  and
Christopher J. Fariss
Get access Rights & Permissions [Opens in a new window]

Abstract

The science of human rights requires valid comparisons of repression levels across time and space. Though extensive data collection efforts have made such comparisons possible in principle, statistical measures based on simple additive scales made them rare in practice. This article uses a dynamic measurement model that contrasts with current approaches by (1) accounting for the fact that human rights indicators vary in the level of information they provide about the latent level of repression, (2) allowing realistic descriptions of measurement uncertainty in the form of credible intervals and (3) providing a theoretical motivation for modeling temporal dependence in human rights levels. It presents several techniques, which demonstrate that the dynamic ordinal item-response theory model outperforms its static counterpart.

Type
Original Articles
Information
Political Science Research and Methods , Volume 2 , Issue 1 , April 2014 , pp. 1 - 31
Copyright
Copyright © Political Science and Research Methods 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*Keith Schnakenberg is a graduate student in the Department of Political Science at Washington University, St. Louis ([email protected]). Christopher Fariss is an Assistant Professor in the Department of Political Science, Pennsylvania State University ([email protected]). We thank Chad Clay, Jesse Driscoll, James Fowler, Jeff Gill, Miles Kahler, David Lake, Yon Lupu, Will Moore, Amanda Murdie, David Richards, Guillermo Rosas and Sebastian Saiegh for helpful comments. Earlier versions of this paper were presented at the 2012 meeting of the Midwestern Political Science Association, the 2012 meeting of the International Studies Association, the 2011 meeting of the American Political Science Association and the 2010 meeting of the Southern Political Science Association. We would also like to acknowledge the Southern Political Science Association for travel grants. The data and code used in this paper and the latent variable estimates from the dynamic models are publicly available at http://dvn.iq.harvard.edu/dvn/dv/HumanRightsScores. Both authors contributed to the study design, data collection, analysis and preparation of the manuscript.

References

Albert, James H.Johnson, Val E.. 1999. Ordinal Data Modeling. New York: Springer-Verlag.Google Scholar
Aleman, EduardoSaiegh, Sebastiáns M.. 2007. ‘Legislative Preferences, Political Parties, and Coalition Unity in Chile’. Comparative Politics 39(3):253–272.Google Scholar
Brysk, Alison. 1994. ‘The Politics of Measurement: The Contested Count of the Disappeared in Argentina’. Human Rights Quarterly 16(4):676–692.Google Scholar
Cingranelli, David L.Richards, David L.. 1999. ‘Measuring the Level, Pattern, and Sequence of Government Respect for Physical Integrity Rights’. International Studies Quarterly 43(2):407–417.Google Scholar
Cingranelli, David L.Richards, David L.. 2010. ‘The Cingranelli and Richards (CIRI) Human Rights Data Project’. Human Rights Quarterly 32(2):401–424.Google Scholar
Cingranelli, David L.Richards, David L.. 2012a. ‘The Cingranelli-Richards (CIRI) Human Rights Data Project Coding Manual Version 2008.3.13’, available at http://ciri.binghamton.edu/documentation/ciri_coding_guide.pdf.Google Scholar
Cingranelli, David L., Richards, David L. 2012b. ‘The Cingranelli-Richards Human Rights Dataset Version 2008.03.12’, available at http://www.humanrightsdata.org.Google Scholar
Clark, Ann MarieSikkink, Kathryn. Forthcoming. ‘Information Effects and Human Rights Data: Is the Good News about Increased Human Rights Information Bad News for Human Rights Measures?’ Human Rights Quarterly.Google Scholar
Claude, Richard P.Jabine, Thomas B.. 1986. ‘Symposium: Statistical Issues in the Field of Human Rights’. Human Rights Quarterly 8(4):551–566.Google Scholar
Clinton, Joshua, Jackman, SimonRivers, Douglas. 2004. ‘The Statistical Analysis of Roll Call Data’. American Political Science Review 98(2):355–370.CrossRefGoogle Scholar
Conrad, Courtenay R., Demeritt., Jacqueline H.R. 2011. ‘Options in the Arsenal: Are Repressive Tactics Substitutes or Complements?’ Working Paper.Google Scholar
Davenport, Christian. 1995. ‘Multi-Dimensional Threat Perception and State Repression: An Inquiry into Why States Apply Negative Sanctions’. American Journal of Political Science 39(3):683–713.CrossRefGoogle Scholar
Desposato, Scott W. 2006. ‘The Impact of Electoral Rules on Legislative Parties: Lessons from the Brazilian Senate and Chamber of Deputies’. Journal of Politics 68(4):1018–1030.CrossRefGoogle Scholar
Donnelly, JackHoward, Rhoda E.. 1988. ‘Assessing National Human Rights Performance: A Theoretical Framework’. Human Rights Quarterly 10(2):214–248.Google Scholar
Duvall, Raymond D.Stohl, Michael. 1983. ‘Governance by Terror’. In The Politics of Terrorism, edited by Michael Stohl, 179–219. New York: Marcel Dekker.Google Scholar
Fariss, Christopher J.Schnakenberg, Keith. 2013. ‘Measuring Mutual Dependence Between State Repressive Actions’. Journal of Conflict Resolution forthcoming.Google Scholar
Gelman, Andrew, Carlin, John, Stern, HalRubin, Donald. 2003. Bayesian Data Analysis, Second Edition. Boca Raton, FL: Chapman and Hall/CRC.Google Scholar
Gelman, AndrewRubin, Donald B.. 1992. ‘Inference from Iterative Simulation using Multiple Sequences’. Statistical Science 7:457–511.Google Scholar
Gelman, AndrewHill, Jennifer. 2007. Data Analysis using Regression and Multilevel/Hierarchical Models. Cambridge, MA: Cambridge University Press.Google Scholar
Geweke, John. 1992. Evaluating the Accuracy of Sampling-based Approaches to Calculating Posterior Moments. In Bayesian Statistics 4, edited by J. M. Bernardo, J. Berger, A. P. Dawid and J. F. M. Smith, 169–193. Oxford: Oxford University Press.Google Scholar
Gill, Jeff. 2007. Bayesian Methods: A Social and Behavioral Sciences Approach, Second Edition (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences), Second Edition. Boca Raton, FL: Chapman and Hall/CRC.Google Scholar
Goodman, RyanJinks, Derek. 2003. ‘Measuring the Effects of Human Rights Treaties’. European Journal of International Law 14(1):171–183.Google Scholar
Heidelberger, PhilipWelch, Peter D.. 1981. ‘A Spectral Method for Confidence Interval Generation and Run Length Control in Simulations’. Communications of the ACM 24(4):233–245.Google Scholar
Heidelberger, PhilipWelch, Peter D.. 1983. ‘Simulation Run Length Control in the Presence of an Initial Transient’. Operations Research 31(6):1109–1144.Google Scholar
Jabine, Thomas B.Claude, Richard P., eds. 1992. Human Rights and Statistics: Getting the Record Straight. Philadelphia: University of Pennsylvania Press.Google Scholar
Jackman, Simon. 2008. ‘Measurement’. In The Oxford Handbook of Political Methodology, edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. New York: Oxford University Press.Google Scholar
Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. New York: John Wiley and Sons.Google Scholar
Kass, Robert E.Raftery, Adrian E.. 1995. ‘Bayes Factors’. Journal of the American Statistical Association 90(430):773–795.Google Scholar
Keck, MargaretSikkink, Kathryn. 1998. Activists Beyond Borders: Advocacy Networks in International Politics. Ithaca, NY: Cornell University Press.Google Scholar
Landman, Todd. 2005. ‘The Political Science of Human Rights’. British Journal of Political Science 35(3):549–572.Google Scholar
Landman, ToddCarvalho, Edzia. 2009. Measuring Human Rights. London: Routledge.Google Scholar
Lauderdale, Benjamin E. 2010. ‘Unpredictable Voters in Ideal Point Estimation’. Political Analysis 18(2):151–171.Google Scholar
Lopez, George A.Stohl, Michael. 1992. ‘Problems of Concept and Measurement in the Study of Human Rights’. In Human Rights and Statistics: Getting the Record Straight, edited by Thomas B. Jabine and Richard P. Claude. Philadelphia: University of Pennsylvania Press.Google Scholar
Martin, Andrew D.Quinn, Keven M.. 2002. ‘Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999’. Political Analysis 10(2):134–153.Google Scholar
McCormick, James M.Mitchell, Neil J.. 1997. ‘Human Rights Violations, Umbrella Concepts, and Empirical Analysis’. World Politics 49(4):510–525.Google Scholar
Meernik, James D., Aloisi, Rosa, Sowell, MarshaNichols, Angela. 2012. ‘The Impact of Human Rights Organizations on Naming and Shaming Campaigns’. Journal of Conflict Resolution 56(2):233–256.Google Scholar
Mislevy, Robert. 1991. ‘Randomization-based Inference about Latent Variables from Complex Samples’. Psychometrika 56(2):177–196.Google Scholar
Murdie, AmandaDavis, David R.. 2012. ‘Shaming and Blaming: Using Events Data to Assess the Impact of Human Rights INGOs’. International Studies Quarterly 56(1):1–16.Google Scholar
Pemstein, Daniel, Meserve, Stephen A.Melton, James. 2010. ‘Democratic Compromise: A Latent Variable Analysis to Ten Measure of Regime Type’. Political Analysis 18(4):426–449.CrossRefGoogle Scholar
Piazza, James A.Walsh, James Igoe. 2009. ‘Transnational Terror and Human Rights’. International Studies Quarterly 53(1):125–148.Google Scholar
Plummer, Martyn. 2010. ‘JAGS (Just Another Gibbs Sampler) 1.0.3 Universal’, available from http://www-fis.iarc.fr/martyn/software/jags/.Google Scholar
Poe, Steven C. 1990. ‘Human Rights and US Foreign Aid: A Review of Quantitative Studies and Suggestions for Future Research’. Human Rights Quarterly 12(4):499–512.Google Scholar
Poe, Steven C.. 1991. ‘U.S. Economic Aid Allocation: The Quest for Cumulation’. International Interactions 16(4):295–316.Google Scholar
Poe, Steven C.. 2004. ‘The Decision to Repress: An Integrative Theoretical Approach to the Research on Human Rights and Repression’. In Understanding Human Rights Violations: New Systematic Studies, edited by S. Carey and S. Poe, 16–42. Aldershot: Ashgate.Google Scholar
Poe, Steven C., Carey, Sabine C.Vazquez, Tanya C.. 2001. ‘How are These Pictures Different? A Quantitative Comparison of the US State Department and Amnesty International Human Rights Reports, 1976–1995’. Human Rights Quarterly 23(3):650–677.Google Scholar
Poole, Keith T. 2005. Spatial Models of Parliamentary Voting. Cambridge, UK: Cambridge University Press.Google Scholar
Poole, Keith T.Rosenthal, Howard. 1991. ‘Patterns of Congressional Voting’. American Journal of Political Science 35(1):228–278.Google Scholar
Poole, Keith T.Rosenthal, Howard.. 1997. A Political-Economic History of Roll Call Voting. New York: Oxford University Press.Google Scholar
Quinn, Keven M. 2004. ‘Bayesian Factor Analysis for Mixed Ordinal and Continuous Responses’. Political Analysis 12(4):338–353.Google Scholar
R Development Core Team. 2011. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing, available from http://www.R-project.org.Google Scholar
Richards, David, Gelleny, RonaldSacko, David. 2001. ‘Money With A Mean Streak? Foreign Economic Penetration and Government Respect for Human Rights in Developing Countries’. International Studies Quarterly 45(2):219–239.Google Scholar
Rosas, Guillermo. 2009. ‘Dynamic Latent Trait Models: An Application to Latin American Banking Crises’. Electoral Studies 28:375–387.CrossRefGoogle Scholar
Rosas, GuillermoShomer, Yael. 2008. ‘Models of Nonresponse in Legislative Politics’. Legislative Studies Quarterly 33(4):573–601.Google Scholar
Rubin, Donald B. 1987. Multiple Imputation for Nonresponse in Surveys. New York: J. Wiley & Sons.Google Scholar
Schenker, NathanielGentleman, Jane F.. 2001. ‘On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals’. The American Statistician 55(3):182–186.Google Scholar
Spiegelhalter, David J., Best, Nicola G., Carlin, Bradley P.Van Der Linde, Angelika. 2002. ‘Bayesian Measures of Model Complexity and Fit’. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64(4):583–639.Google Scholar
Stohl, Michael, Carleton, David, Lopez, GeorgeSamuels, Stephen. 1986. ‘State Violation of Human Rights: Issues and Problems of Measurement’. Human Rights Quarterly 8(4):592–606.Google Scholar
Treier, ShawnJackman, Simon. 2008. ‘Democracy as a Latent Variable’. American Journal of Political Science 52(1):201–217.Google Scholar
Voeten, Erik. 2000. ‘Clashes in the Assembly’. International Organization 54(2):185–215.Google Scholar
Wood, Reed M.Gibney, Mark. 2010. ‘The Political Terror Scale (PTS): A Re-introduction and Comparison’. Human Rights Quarterly 32(2):367–400.Google Scholar