Fake news : les bibliothécaires du Québec veulent faire partie de l’équation
Bibliographic record
Abstract
Cette enquête présente les perceptions de la communauté des bibliothécaires professionnels du Québec face aux fake news et les initiatives que celle-ci a mis en place pour lutter contre la désinformation. Au moyen d’un questionnaire en ligne soumis durant l’été 2020, auquel 263 bibliothécaires provenant de divers milieux d’exercice ont répondu, la consultation révèle que la quasi-totalité des bibliothécaires se préoccupent de la présence des fake news dans le paysage médiatique. Pour freiner les fake news, l’éducation aux médias et à l’information est une solution qui fait consensus, mais le recours aux lois reçoit un accueil mitigé. Grâce aux commentaires reçus, l’enquête met en lumière de nombreuses initiatives locales et nationales visant à sensibiliser la population aux dangers de la désinformation et lui donner des outils pour éviter de tomber dans le panneau. En conclusion, les auteurs encouragent les bibliothécaires à intervenir davantage sur la place publique, notamment en faisant valoir leur expertise, car celle-ci peut être utile à l’ensemble des citoyens.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".