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Record W2953751221 · doi:10.7202/1067431ar

Leçons de l’élection présidentielle camerounaise de 2018

2019· article· fr· W2953751221 on OpenAlexvenueno aff
Danielle Minteu-Kadje, Christophe Prémat

Bibliographic record

VenueSens public · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Geopolitics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesEthnologySociologyArt

Abstract

fetched live from OpenAlex

L’article se propose d’élaborer une anthropologie de l’État camerounais afin de comprendre les enjeux politiques de la dernière élection présidentielle de 2018 et le rendez-vous manqué du multipartisme au début des années 1990. Dans une perspective postcoloniale, il semble que le Cameroun se soit réorganisé autour d’un État unitaire francophone pour consolider le pouvoir d’une élite en place. L’article décrit les mécanismes de cette réification en s’appuyant sur les textes constitutionnels et les institutions chargées de protéger le statu quo. Il revient également sur les défis géopolitiques que constituent le groupe terroriste Boko Haram et la gestion de la crise de la partie anglophone. Ces menaces tendent à renforcer l’État unitaire et sécuritaire au détriment d’un débat politique sur l’avenir du Cameroun.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.024
GPT teacher head0.285
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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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