Bibliographic record
Abstract
This paper examines the profound and steady influence of aid and aid modalities on the education agenda in Africa and argues that, ultimately, the broader intent of Education for All as advocated at Jomtien and Dakar was narrowed to an almost singular focus on Universal Primary Education. This narrowing phenomenon is attributed to donor obsession with targets and comes at the expense of true ownership while compromising quality and upstream linkages in the education systems of Tanzania and other African countries. The paper concludes with some of the lessons learned and possible future orientations of aid to education for development. Cet article examine l’influence profonde et constante de l’aide et de ses modalités dans l’agenda éducatif en Afrique et soutient qu’en définitive, l’objectif plus général de l’Éducation pour Tous telle que préconisée à Jomtien et à Dakar a été réduit à une quasi-singulière concentration sur l’Éducation Primaire Universelle. Ce rétrécissant phénomène est attribué à l’obsession des bailleurs de fond avec des objectifs et survient au détriment d’une véritable appropriation, tout en compromettant la qualité et les liens réalisés en amont dans les systèmes éducatifs en Tanzanie et d’autres pays africains. Cet article conclue en soulignant quelques-unes des leçons apprises et les possibles orientations futures de l’aide à l’éducation pour le développement.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".