L’École de bibliothéconomie et des sciences de l’information (EBSI) de l’Université de Montréal 1961-2003 : quatre décennies de formation des spécialistes de l’information au Québec et au Canada français
Bibliographic record
Abstract
L’École de bibliothéconomie a été fondée en 1961 pour fournir au Québec et au Canada de langue française des bibliothécaires professionnels dans un premier temps, puis dans les décennies suivantes, des professionnels de l’information et des archivistes. Après plus de quatre décennies de fonctionnement, on peut maintenant dire qu’elle a atteint une maturité certaine. L’objectif de ce texte est de souligner les points importants de son évolution et de montrer sa contribution à la formation du personnel professionnel en bibliothéconomie, en sciences de l’information et en archivistique au Québec, au Canada de langue française et dans la francophonie, depuis plus de quarante ans.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.023 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".