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separating dirty war from dirty peace: revisiting the conceptualization of state repression in quantitative data

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Abstract

What is state repression? This article explores in detail how state repression is conceptualized by the two most prevalent data sets employed by qualitative scholars: the Political Terror Scale (PTS) and the Cingranelli-Richards (CIRI) data set. The article uses disaggregated data on the characteristics of state’s repressive strategy and compare changes in these subcomponents in years when the overall measure of repression increases or decreases. Following bivariate and multivariate analyses of eighteen West African countries with a history of fluctuating human rights practices, the article finds that both the PTS and CIRI scores are primarily influenced by military involvement in human rights violations. The article highlights the need for more scholarship on the mechanisms behind the finding that democracies are less repressive than other regimes and motivates more studies on how and when repression decreases.

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Notes

  1. While there is no consensus regarding what constitutes ‘repression’, throughout this article I define it as the abuse of human rights and use the terms interchangeably.

  2. The role of overt–covert repressive actions is primarily discussed in the Web Appendix of Sullivan (2015).

  3. For a more comprehensive review, see Davenport and Inman (2012).

  4. PTS have a 5-year average intercoder reliability score of 0.85 for 2004–2008, while CIRI report a Krippendorff r-bar reliability statistic of 0.94 for 2004 (Cingranelli and Richards, 2010; Wood and Gibney, 2010).

  5. For a more detailed account of the data collection practices of Amnesty and US SD over time, see Poe et al (2001), Hill et al (2013), and Clark and Sikkink (2013).

  6. Disappearances are by definition difficult to attribute to a perpetrator, and prison guards would of course be involved in all cases of political imprisonment.

  7. By covering a subregion with much within-case variation over a longer time period, the advantage is that the estimations from the data is not unduly influenced by either cases of consistently low levels of repression (such as Norway) or high levels of repression (such as Myanmar).

  8. This include two democratizations in Mali with authoritarian backslide in-between, in 1992 and 2000.

  9. Regression output and robustness tests are available in the Web Appendix.

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Acknowledgements

This research was funded by the Swedish Research Council (2010-1514) ‘Government Repression: The Targets, Strategies, and Patterns of State Human Rights Abuse’, and benefited from ENCoRe (European Network of Conflict Research) (COST Action IS1107). The author is grateful to Niklas Karlén for data collection assistance, and input from Kristine Eck, Mihai Croicu, Jacqueline DeMerritt, Courtney Conrad, Christian Davenport, Chris Farriss, and two anonymous reviewers which have strengthened this project and article.

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  1. Department of Peace and Conflict Research, Uppsala University,

    joakim kreutz

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kreutz, j. separating dirty war from dirty peace: revisiting the conceptualization of state repression in quantitative data. Eur Polit Sci 14, 458–472 (2015). https://doi.org/10.1057/eps.2015.63

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