Bibliographic record
Abstract
Ce dossier traite des sciences de l’information au Québec, de leur évolution croissante et de leur nouvel ancrage dans la profession, la communauté et divers organismes. Depuis les deux dernières décennies, l’arrivée de l’internet, l’évolution exponentielle des technologies de l’information et l’entrée des milleniums, les sciences de l’information ont vécu un véritable séisme bousculant les disciplines traditionnelles telles que la bibliothéconomie et l’archivistique. Les professionnels de l’information au Québec ont emboîté le pas. Des disciplines telles que la gestion de l’information stratégique, la gestion des connaissances, la maitrise des métadonnées, l’exploitation du web sémantique, l’analyse de données et l’intelligence artificielle ont alors été progressivement introduites dans la formation. Parallèlement, les métiers en sciences de l’information au Québec ont connu une transformation significative marquée par l’introduction et l’application de pratiques professionnelles telles que les sciences sociales et le marketing, la gestion de projet ou les interventions spécifiques dans les milieux communautaires.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
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".