Replication data for: New Evidence that Naming and Shaming Influences State Human Rights Practices
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication data for: New Evidence that Naming and Shaming Influences State Human Rights Practices
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Identifier |
https://doi.org/10.7910/DVN/1UIFQR
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Creator |
Zhou, Yuan
Kiyani, Ghashia Crabtree, Charles |
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Publisher |
Harvard Dataverse
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Description |
To what extent does naming and shaming influence state respect for human rights? While many countries and international human rights organizations strategically name and shame states with the hope of deterring human rights abuses, prior empirical work on these strategies disagrees about their effectiveness. In this article, we re-investigate this theoretically important question. We take a new approach to examining how naming and shaming influences state human rights practices. First, we apply automatic text analysis to a corpus of human rights reports and develop two new cross-national human rights naming and shaming measures. One measure focuses on Amnesty International’s (AI) naming and shaming efforts, while the other focuses on the United States government. Second, we assess the construct validity of these measures, finding evidence that they capture the relevant latent dimension. Third, we examine the extent to which these measures are correlated with human rights practices. Our results show that while AI's naming and shaming activities do not seem to influence regime practices, the State Department's are associated with improved rights performance. Our measures and results contribute to the growing literature on human rights, international organizations, and foreign policy.
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Subject |
Social Sciences
Human Rights |
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Date |
2024-02-23
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Contributor |
Zhou, Yuan
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