Tracking the Money for Open Educational Resources in South African basic Education: What We Don’t Know
Bibliographic record
Abstract
Limited research has been done to date on the extent of public funding of Open Educational Resources (OER) within basic education (K-12 equivalent) in South Africa. As claims have been made about the potential cost reductions that come with using OER, this study aimed to establish a benchmark of public spending on educational resources, uncover how much is being spent on OER and assess cost-savings of OER adoption. A desk review and document analysis of official information sources on South African basic education was conducted to develop a conceptual understanding of funding allocations the South African government uses for educational resources. A review of publicly available government reports and budgets showed that there is insufficient information at this time to determine how much is being spent on OER specifically or to act as a benchmark for potential cost savings of OER. This study highlights the information gaps which would need to be filled in order to make claims about OER and their potential as cost savers.
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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 | 0.010 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.021 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".