Développer une littératie critique en enseignement face aux défis du 21e siècle. Ou de l'importance d'enseigner un rapport critique au numérique à l'ère des infox
Bibliographic record
Abstract
Le présent chapitre propose de revisiter le concept de pensée critique, abordée en relation avec la culture informationnelle, en étudiant comment celles-ci sont évoquées dans les documents gouvernementaux. Si l’objectif est de développer une forme de citoyenneté en contexte numérique, plusieurs limites sont relevées, notamment en ce qui concerne la portée politique, qui semble restreinte. Nous suggérons de rapprocher davantage la pensée critique et la culture informationnelle en s’appuyant sur la notion de littératie critique. Plusieurs principes pédagogiques sont enfin présentés afin de donner corps à cette proposition, notamment dans le but d’interroger le rapport au pouvoir et d’encourager la réflexion, la transformation et l’action.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".