Cost-Sharing in Higher Education in Tanzania: The Experiences of the 1990s and One Decade Later
Bibliographic record
Abstract
This article discusses the cost- sharing experiences of 73 Tanzanian female undergraduates who took part in a 1997 study. It also integrated views and suggestions of the 2007 students from the University of Dar es Salaam and Sokoine University of Agriculture, Mazimbu campus. The University of Dar es Salaam was closed in 2007 because First Year students boycotted classes to protest the government’s policy that required them to pay 40% for their higher education. I advocate for partnership in student financing and the introduction of graduate tax for recovering higher education students’ loans. Cet article traite les expériences du partage des coûts de 73 tanzaniennes du premier cycle qui ont pris part à une étude en 1997. Il a également intégré les avis et les suggestions des étudiants de 2007 venant de l’Université de Dar es Salaam et de l’Université d’agriculture Sokoine du campus de Mazimbu. L’Université de Dar es Salaam a été fermée en 2007 car les étudiants de première année ont boycotté les cours afin de protester contre la politique du gouvernement qui leur a exigé de payer 40 % des frais pour l’enseignement supérieur. Je préconise un partenariat de financement des étudiants ainsi que l’introduction d’un impôt gradué afin de recouvrir les prêts des étudiants de l’enseignement supérieur.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".