Bibliographic record
Abstract
The paper reports on a qualitative case study of one high school library. It forms part of a broader study of the Bookery’s School Library Project which has established 40 libraries in disadvantaged schools in Cape Town. The paper examines what difference the library is making to the school. The overarching aim is to find what might be learned from the Bookery’s Library Assistant (LA) programme about the staffing of school libraries in the South African context, where fewer than 20% of schools have functional libraries. The case study over two weeks comprised observations, interviews, and a questionnaire survey of the teachers. The working relations between the Bookery library assistant and the “teacher-librarian”, a full- time class teacher and the library’s driving force, are found to be crucial to the library’s sustainability. The library is clearly playing an important role in the students’ school experience and in meeting the information needs of teachers in their classroom teaching. But, despite general beliefs that the library is “a good thing”, only a minority of teachers integrate it into their teaching. It seems that teachers lack insight into the role of a library and information literacy in 21st century learning. Other key restrictions on the fulfilment of the library’s potential are its limited collections and the lack of ICTs. In the words of one participant, the overall conclusion is that “ It is helping but there are limitations”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".