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Record W2479906894 · doi:10.1017/s0069005800011061

More Honey Than Vinegar: Peer Review As a Middle Ground between Universalism and National Sovereignty

2014· review· en· W2479906894 on OpenAlexvenueno aff
Elvira Domínguez-Redondo, Edward McMahon

Bibliographic record

VenueCanadian Yearbook of international Law/Annuaire canadien de droit international · 2014
Typereview
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsUniversalismHuman rightsSovereigntyPolitical scienceLaw and economicsAdversarial systemMaturity (psychological)Conceptual frameworkCompliance (psychology)LawSociologyPsychologySocial psychologySocial science

Abstract

fetched live from OpenAlex

Summary Peer review mechanisms, such as the Universal Periodic Review, rely upon traditional sovereign state diplomacy for contemporary human rights implementation. This article argues that this is a positive development for several reasons. First, at a theoretical level, it reveals an evolving maturity of the human rights regime through its capacity to detach from exclusively legalistic approaches to human rights implementation. Second, at a policy level, there is enough evidence of measured positive outcomes of peer review mechanisms to suggest a preference for more co-operative approaches to ensuring human rights compliance as a first and complementary step to other more controversial legal/adversarial means of implementation (such as the third pillar of the R2P concept). Finally, peer review mechanisms offer a theoretical and pragmatic framework conciliating between universalist and relativist conceptual approaches to human rights, accommodating and integrating views that call for compliance with international human rights law as well as those emphasizing respect for sovereignty.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.102
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.007
Scholarly communication0.0080.008
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.002

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 head0.027
GPT teacher head0.313
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
GenreReview

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

Citations18
Published2014
Admission routes1
Has abstractyes

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