An Analysis of Higher Education Policy Act 101 of 1997
Bibliographic record
Abstract
The South African higher education sector is one of the most contested sectors with high policy influxes since the beginning of current democratic dispensation. From a horrendous past where it endured the repressive strategy that disenfranchised majority of the population, the country’s higher education system undoubtedly needed a thorough reshape to meet the then changing national development needs and aspirations of the newly elected democratic government. Hence, the prime strategy of redressing past imbalances and inequalities accruing from pre-democratic era, was justified through Higher Education Policy (HEP) Act 101 – whose operational consistency is evident in the past twenty-five years. This synoptic review focuses on HEP Act 101 by unravelling the circumstances presaging its formation, the policy provisions and amendments – whose sectional highlights are also embodied herein. The brief prelude to the policy’s penultimate silver-jubilee forms an agendum for extensive research on its performance over the last quarter-century, while the ensuing discourse aims to channel scholarly attention on critical matters that may inform a new HEP formation or amendment, that will be more agreeable with contemporary socioeconomic needs of the masses and synchronous to new national development goals in the long run.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".