Respecting Human Rights: Does Treaty Ratification Lead to Compliance?
Bibliographic record
Abstract
Since the nonbinding Universal Declaration of Human Rights, states have created treaties and conventions to outline what is or is not acceptable regarding the treatment of human beings, with the understanding that if a state signs and ratifies these documents then that state will comply with the principles outlined within it. Time and again however, compliance, or the lack thereof, has presented as a concern amongst many states, as well as non-state actors. The issue of compliance is a serious one because it speaks to credibility. If states do not anticipate compliance from one another it undermines the entire international system and any structure that has been created to address the anarchic nature of international relations will dissolve. In order to make analysis of this massive issue area manageable, I focus on state compliance with human rights law and more specifically, compliance with the Indigenous and Tribal Peoples Convention 1989, or C169. Both Brazil and Argentina have signed and ratified C169 and both are democratic with indigenous populations. Comparing these two states it allows us to better ascertain the circumstances under which states may comply with or defect from international human rights law. I provide an overview on what rationalist theories suggest about compliance, followed by constructivist views. I then outline my position before examining the results of the case study and assessing its’ impact as related to both theory and my arguments. Ultimately, I find that notwithstanding ratification and well-developed democratic institutions that allow for a strong civil society to participate in politics, there are still circumstances wherein a state will defect from a human rights treaty because the gain of doing so outweighs the cost of non-compliance.
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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 | 0.040 | 0.124 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".