Chapitre 11. Gilbert Paquette
Bibliographic record
Abstract
Titulaire d’une these en Intelligence artificielle et Education soutenue en 1991 a l’universite du Mans sous la direction de M. Vivet, le Quebecois G. Paquette appartient au courant de la recherche en informatique pedagogique dont, en France, E. Bruillard et M. Grandbastien comptent aujourd’hui parmi les representants les plus actifs. Depuis 2001 il est titulaire de la Chaire de recherche du Canada en Ingenierie cognitive et educative a la Tele-universite du Quebec (Teluq) ; dans le prolongement de ses travaux anterieurs (dont il sera question ici), ceux qu’il mene actuellement ont trait aux systemes de gestion des ressources educatives libres. Il est l’auteur de nombreux articles scientifiques et de sept ouvrages, parmi lesquels celui sur l’ingenierie pedagogique, paru en 2002, d’ou sont tires les extraits ci-dessous.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.082 | 0.041 |
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".