Appropriations de la decentralisation et regulation des systemes educatifs en Afrique subsaharienne : Une analyse comparee des cas du Benin et du Senegal
Bibliographic record
Abstract
Cette recherche analyse la régulation des systèmes éducatifs du Bénin et du Sénégal dans le cadre de la décentralisation de l’éducation qui leur a été prescrite à travers les politiques d’ajustement structurel. Quatre aspects clés du système éducatif ont été analysés: l’offre d’éducation, les programmes d’enseignement, l’inspection et/ou le contrôle des enseignants et la condition enseignante. L’étude de cas à partir de données invoquées a été utilisée. Il ressort de l’analyse comparée des portraits nationaux que les appropriations nationales de la mise en application de la décentralisation demeurent assez distinctes dans ces deux pays et que la régulation actuelle de leurs systèmes éducatifs repose sur un modèle composite. This paper analyzes the regulation of education systems in Benin and in Senegal in the context of decentralization as prescribed through the structural adjustment policy. Four key elements of the education system are considered: access, curriculum, inspection and, or supervision of teachers, and teaching conditions. The author develops a case study from the available data. The comparative analysis of the national profiles demonstrates that applications of the decentralization process are quite different between these two countries and that the current regulation of the education systems is built on a composite model.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".