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Measuring human rights abuse from access to information requests

Ellington, Sarah A. V., Bagozzi, Benjamin E., Berliner, Daniel ORCID: 0000-0002-0285-0215, Palmer-rubin, Brian and Erlich, Aaron (2022) Measuring human rights abuse from access to information requests. Journal of Conflict Resolution, 66 (2). 357 - 384. ISSN 0022-0027

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Identification Number: 10.1177/00220027211035553


Existing measures of human rights abuses are often only available at the country-year level. Several more fine-grained measures exhibit spatio-temporal inaccuracies or reporting biases due to the primary sources upon which they rely. To address these challenges, and to increase the diversity of available human rights measures more generally, this study provides the first quantitative effort to measure human rights abuses from textual records of citizen-government interactions. Using a dataset encompassing over 1.5 million access-to-information (ATI) requests made to the Mexican federal government from June 2003 onward, supervised classification is used to identify the subset of these requests that pertain to human rights abuses of various types. The results from this supervised machine learning exercise are validated against (i) gold standard ATI requests pertaining to past human rights abuses in Mexico and (ii) several accepted external measures of sub-national and sub-annual human rights abuses. In doing so, we demonstrate that the measurement of human rights abuses from citizen-submitted ATI request texts can provide measures of human rights abuse that exhibit both high validity and notable spatio-temporal specificity, relative to existent human rights datasets and variables.

Item Type: Article
Official URL:
Additional Information: © 2021 SAGE
Divisions: Government
Subjects: J Political Science > JC Political theory
J Political Science > JZ International relations
Date Deposited: 05 Oct 2021 14:09
Last Modified: 16 May 2024 22:15

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