Leçons de l’élection présidentielle camerounaise de 2018
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".