Measuring Human Rights Abuse from Access to Information Requests
Bibliographic Data
| ID | 10071783 |
|---|---|
| Authors | Sarah A V Ellington (0000-0003-1491-675X, University of Delaware), Benjamin E Bagozzi (0000-0002-6233-6453, University of Delaware, corresponding author), Daniel Berliner (0000-0002-0285-0215, London School of Economics and Political Science), Brian Palmer-Rubin (0000-0003-4280-7251, Marquette University), Aaron Erlich (0000-0001-6571-9081, McGill University) |
| Year | 2021 |
| Volume | 66 |
| Issue | 2 |
| Pages | 357-384 |
| Publication date | 2021-09-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Conflict Resolution (JOURNAL) |
| Journal identifiers | ISSN: 0022-0027 • E-ISSN: 1552-8766 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/00220027211035553 |
| OpenAlex | W3203304734 |
| Language | EN |
| References cited | 35 |
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
Diversity (politics · Government (linguistics · Human rights · Political science · Corruption and Economic Development · Judicial and Constitutional Studies · Law · Local Government Finance and Decentralization
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| Citation velocity | historical |
|---|---|
| Highly cited | No |