Signaling commitments, making concessions: Democratization and state ratification of international human rights treaties, 1966–2006
Bibliographic record
Abstract
How is the establishment of the international human rights regime possible in the first place? Bringing together theories from international law, political science, and sociology, I revisit the argument that global efforts to institutionalize human rights into international law are mainly driven by states undergoing democratization. Political democratization is crucial to the creation of the international human rights regime, because it generates “commitment” and “concession” mechanisms that motivate states to support human rights treaties. Analyzed by Cox event history models, the data on state ratification of the core United Nations human rights treaties from 1966 through 2006 are consistent with this argument. Improvement in human rights and increased political competition do significantly increase the rate of state ratification of human rights treaties. The ratification-promoting effect of democratization also operates in an immediate fashion. Overall, this study provides empirical support for the dynamic state-oriented explanation for global legalization of human rights and suggests a close connection between global democratization waves and the establishment of the human rights regime.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".