Bibliographic record
Abstract
In this paper I consider the politics around the school library in South Africa and what is emerging during this postapartheid period of social transformation, to assess the politics of the 'new space' being produced through that transformation. This requires me to look back, through memories and images, at what was inherited from the apartheid era – an approach often criticised by embarrassed white South Africans who wish to be blinkered, and move on, ignoring our painful history, our roots. Then I revisit the process of formulating national regulatory policy for school libraries in South Africa, and try to understand the obstacles to its progress. My conclusions will point to what we might need to look for in the emerging policy for a ‘new practice’ and ‘new space' for school libraries.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.027 | 0.038 |
| Scholarly communication | 0.036 | 0.036 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 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".