Student Funding Model Used By the National Student Financial Aid Scheme (Nsfas) at Universities in South Africa
Bibliographic record
Abstract
Purpose: The purpose of this research is focused on evaluating NSFAS as student funding at South African Universities. Problem Investigated: Public universities in South Africa witnessed student protests on campuses during 2015 and 2016. These were orchestrated by students demanding additional funding assistance from the National Student Financial Aid Scheme (NSFAS), zero-fee increases and the scrapping of student debt by universities. In 2012 a report for fee-free university education for poor people was handed to the Minister of Higher Education and Training. It suggested that fee-free higher education would be possible if more funds were injected into the NSFAS. It is not currently known how much funding is required to fund both the poor students and the missing middle students who earn beyond the NSFAS eligibility threshold. Methodology: A quantitative research method was used. Information on student funding at a specific period, was collected using different universities to corroborate the data received in order to solve the research problem. The approach assisted in identifying how student funding is allocated per university in a specific academic year. Value of the research: The higher education sector is constantly evolving. The past struggle of universities was to ensure that they attracted the best academics and students. The focus has now changed to the student struggle on matters of academic exclusion, financial exclusion and the decolonizing of universities. The study of student funding in South African universities is made more urgent by student protests at universities, and the citing of lack of funding as the main reason why students have been excluded from the universities. The study focuses on the real impact on the universities and also how they have responded to the major challenges. Conclusion: Although this study focused mainly on student funding, it is critical that students who are funded from various sources are also supported in terms of psychological readiness, the transition from matric to university and acquiring financial management skills.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".