La collaboration entre bibliothécaires et technicien·ne·s en documentation : défis, opportunités et bonnes pratiques en bibliothèques universitaires et spécialisées
Bibliographic record
Abstract
Cet article étudie comment la collaboration entre bibliothécaires et technicien·ne·s en documentation au sein des bibliothèques académiques et spécialisées peut être renforcée et réinventée. Par l’analyse d’une revue de la littérature et d’études de cas, les auteur·e·s identifient les défis qui freinent la coopération interprofessionnelle, les bonnes pratiques qui mènent à la réussite de projets collaboratifs et les bénéfices d’une approche collaborative. Cet article souhaite ainsi ajouter une pierre à l’édifice de la coopération en milieux documentaires afin de démontrer que les professionnel·le·s de l’information – et leurs communautés desservies – ont tout à gagner à s’entraider et à s’élever mutuellement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.020 | 0.041 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.062 | 0.150 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; both teacher heads agree on what is shown here.
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".