Model School Libraries: Tools or Threats? Reflections on a Development Project in Sweden
Bibliographic record
Abstract
This article presents reflections on the evaluation ofa school library development project in the county of Orebro, Sweden. Each of six project schools was to create a model library of its own, tailored to the needs and wishes of that particular school. The main conclusions of the analysis of differences between the schools, in terms of project outcomes, indicate that school libraries may be purposeful tools for teaching and learning, but that they may also be experienced as threats by teachers who prefer traditional teaching. The complex process of information seeking and information use for learning raised serious questions with teaching implications for both librarians and teachers, Teaching teams as well as the principal's conceptions of library functions interacted closely with progress in methodological change and input of resources. Public and school libraries found common strategic interests in the development of the model 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 | 0.063 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.018 | 0.017 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".