Abstract
Building on an independent database of 180,000 UN recommendations and a novel computational method, we present the most comprehensive study of human rights (HR) debates to date. We develop a unique empirical model that measures topical density of discourse. This innovative instrument measures the discursive activity of UN HR bodies through a machine-learning textual analysis of their outputs, offering a dynamic map of evolving trends in human rights, both over time (diachronically) and across different mechanisms (synchronically) within the UN HR ecosystem. Leveraging this comprehensive dataset and sophisticated computational methodologies, we identify which protected groups are central to different mechanisms' attention and highlight the major human rights issues that have witnessed significant changes in attention. Our research presents significant findings on the density of UN HR discourse and its implications for two major debates in the field of HR law-HR proliferation and the structural critique of UN HR bodies.
| Original language | English |
|---|---|
| Article number | ngae021 |
| Journal | Human Rights Law Review |
| Volume | 24 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Dec 2024 |
Bibliographical note
Publisher Copyright:© The Author(s) [2024].
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- United Nations human rights bodies
- human rights
- human rights proliferation
- international human rights institutions
- natural language processing
- structural critique of the United Nations
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