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Record W2282464724 · doi:10.7202/1100695ar

FOSTERING COMPLIANCE WITH WOMEN’S RIGHTS IN THE INTER-AMERICAN SYSTEM

2023· article· en· W2282464724 on OpenAlexvenueno aff
Rebecca J. Cook

Bibliographic record

VenueRevue québécoise de droit international · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCompliance (psychology)Political sciencePsychologySocial psychology

Abstract

fetched live from OpenAlex

This article explores why the practice of states in the Americas has been slow to comply with the human rights of women since the adoption of the American Declaration of the Rights and Duties of Man in 1948. The article explains that since states tend to obey international law as a result of repeated interaction among transnational actors, a first step toward fostering compliance is to empower more actors concerned with women, particularly marginalized women, to participate in the process. A next step is to explore how the available forums at both the regional and international levels have been and could be used to apply human rights to the harms experienced by women. Consistent with this step, the article reviews the case law concerning women developed by the Inter-American Court of Human Rights, the Inter-American Commission on Human Rights and the international treaty bodies. A third step toward fostering compliance is to assess strategies of how best to internalize women’s rights into domestic laws, policies and practices. Pursuant to this step, the article identifies some of the key concluding observations in the country reports of treaty bodies, and notes that most states have yet to change their laws to comply with these observations. The article concludes by examining how sanctions and rewards, or a mixture of the two, could be used to improve compliance with the human rights of women in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.302
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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