CIVIL SOCIETY INTERACTIONS WITHIN THE INTER-AMERICAN INSTITUTIONAL FRAMEWORK: TWO CASE STUDIES IN PROMOTING THE STRENGTHENING OF THE REGIONAL HUMAN RIGHTS SYSTEM
Bibliographic record
Abstract
This paper is an attempt to partly address the question of the impact, on the inter-American human rights system, of non-state actors interacting within the institutional structure of the Organizations of American States (OAS). It reflects the perspective of Rights & Democracy, a Canadian institution with an international mandate to promote democracy by supporting the full realization of all human rights. Rights & Democracy has supported civil society human rights organizations in their battle for a stronger regional human rights system, and a more participatory OAS. The paper first reviews the formal inter-American structure for civil society participation, then submits what is meant to be an empirical contribution. It describes two concrete civil society participation experiences aiming to strengthen the enforcement of inter-American human rights norms: the ongoing process carried out by the International Coalition of Organizations for Human Rights in the Americas, and the actions undertaken by indigenous peoples within the framework of the negotiations surrounding the Draft American Declaration on the Rights of Indigenous Peoples. The paper ends with some concluding remarks on a mitigated assessment of civil society participatory mechanisms within the OAS.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.036 | 0.032 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".