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Record W2741427053 · doi:10.1515/ldr-2017-0022

Creating an anti-corruption norm in Africa: Critical reflections on legal instrumentalization for development

2017· article· en· W2741427053 on OpenAlexaff
Paul D. Ocheje

Bibliographic record

VenueThe Law and Development Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of WindsorYork University
Fundersnot available
KeywordsNormativeLanguage changeNorm (philosophy)Legal normContext (archaeology)Political scienceLaw and economicsValue (mathematics)LawSociologyDevelopment economicsPolitical economyEconomics

Abstract

fetched live from OpenAlex

Abstract This article reflects critically on the instrumental value of law in the anti-corruption struggle in Africa. Three questions are central to this reflection: (a) Is the instrumental use of law to achieve a developmental purpose, such as anti-corruption, defensible in theory and practice? (b) Is law necessary to, and/or adequate for, the creation of an anti-corruption norm? (c) Why do the developing countries perform so poorly in the fight against corruption in comparison with their wealthier, industrialized counterparts? While the article defends the instrumentalization of law in this regard, it argues that the African normative context of corruption throws up peculiar challenges. The article suggests that these challenges must be confronted in order to liberate the full potential of law in the struggle against corruption.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
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 head0.166
GPT teacher head0.424
Teacher spread0.259 · 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.

Study designNot applicable
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

Citations3
Published2017
Admission routes1
Has abstractyes

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