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Record W4200480353 · doi:10.1163/17087384-bja10060

The Socialization of Human Rights and the African Human Rights Action Plan: Issues, Challenges and Opportunities

2021· article· en· W4200480353 on OpenAlexafffundvenue
Ibironke T. Odumosu-Ayanu, Obiora Chinedu Okafor, Sylvia Bawa

Bibliographic record

VenueAfrican Journal of Legal Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsYork UniversityUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSocializationHuman rightsAction (physics)Political scienceAction planSociologyInternational human rights lawLawSocial scienceEconomics

Abstract

fetched live from OpenAlex

Abstract This article critically analyzes human rights socialization in Africa through the lens of the draft African Human Rights Action Plan (AHRAP). It argues that the AHRAP presents a framework for human rights socialization, and it speaks to human rights socialization in distinctive ways. The article demonstrates that the AHRAP relies on African and international influences and seeks to propagate norms inspired by these influences. It analyzes three key issues from the AHRAP and discusses how those issues shape understanding of continental human rights socialization in Africa. These issues are the multiple roles and positions of the African Union, the identity of actors to whom socialization processes apply or ought to apply, and the nature of norms which are the focus of socialization efforts. The article’s analysis of these issues along with the AHRAP’s reliance on African and other influences reveal a path for human rights socialization in Africa that is both challenging and promising.

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)0.033
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.054
Scholarly communication0.0140.014
Open science0.0010.009
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.167
GPT teacher head0.366
Teacher spread0.199 · 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.

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
Published2021
Admission routes3
Has abstractyes

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