Bibliographic record
Abstract
In Portugal, the School Libraries Network program (SLN) has been promoting and sharing best practices through the Web as a way to illustrate the excellent work many libraries do and to inspire others that are in different development stages. These are innovative, consistent, systematic and proven experiences, able to reveal the full use of library resources and potential beyond the four walls of classrooms and the boundaries of schools. The projects and activities focus on different areas: reading, information, media, ICT, curriculum collaboration..., and are disseminated through short videos, synopses, and supporting materials. The work done by the Portuguese school libraries has undoubtedly influenced the progression of reading, evidenced in the recent PISA results (2015). Three years after extensive promotion of these good examples, we can conclude that this has been one of the most effective SLN strategies for the ongoing development of libraries and their impact on learning.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.033 | 0.014 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".