Les politiques de développement de collection dans les bibliothèques annexes de l’ICIST
Bibliographic record
Abstract
Les annexes de l’ICIST (Institut canadien de l’information scientifique et technique) ont établi des politiques de développement de collection en suivant un modèle commun. Chaque politique comprend les sections suivantes : introduction, énoncés de mission du ou des instituts et de l’annexe, sélection, acquisition, gestion de la collection et calendrier de révision de la politique. La sélection est généralement effectuée par le bibliothécaire en chef avec la participation des autres membres du personnel et des usagers. La sélection se fait selon plusieurs critères, soit le sujet, la langue, l’année de publication et le format du document. La gestion de la collection couvre des sujets comme le remplacement des documents, les procédures de conservation et l’élagage. Les politiques constituent un outil essentiel pour une gestion efficace des collections des annexes de l’ICIST.
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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 | 0.033 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.020 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.026 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 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".