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Record W1004993825 · doi:10.1017/cbo9780511494048.003

Conventional conceptions of the African system for the promotion and protection of human and peoples' rights

2007· book-chapter· en· W1004993825 on OpenAlexaff
Obiora Chinedu Okafor

Bibliographic record

VenueCambridge University Press eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsYork University
Fundersnot available
KeywordsPromotion (chess)Human rightsPolitical scienceEnvironmental ethicsEconomic growthLawPhilosophyEconomicsPolitics

Abstract

fetched live from OpenAlex

What I want to do in this chapter is to show that the African system has been imagined in very similar ways as other IHIs. First, I want to show that in their attempt to understand this system, most commentators have viewed it (or one or the other of its component entities) as (a) particularly weak and ineffectual, and (b) as dysfunctional in the sense that it has not served as a panacea to Africa's human rights problems. Secondly, I want to show also that most commentators have viewed the textual/organizational reform of the African system not merely as important, but as the key, to the success of the system. And finally, I want to show that the relevant body of scholarship has, for the most part, either been overly “enforcement-centred” or excessively focused on the “voluntary compliance” analytical framework. As has been noted already, this assessment of the conventional approaches does not imply that the state compliance optic is wrong in itself. Rather, it is intended to underscore its conceptual incompleteness and the necessity for its enlargement and expansion. What will be suggested is that there is a need to reach beyond – while retaining – the state compliance-focused optic. Having already considered in chapter 2, the various approaches to the study of IHIs more generally, and having concluded that the constructivist approach best serves our purposes in this book, that whole discussion will not be repeated here.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.997
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.054
GPT teacher head0.249
Teacher spread0.195 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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