Bilan d’une première décennie de travaux sur l’intersection de la citoyenneté politique, de la citoyenneté numérique et de la « news literacy ». Une recension des écrits publiés entre 2005 et 2017
Bibliographic record
Abstract
Cet article présente les conclusions d’un état des connaissances et une proposition d’articulation des concepts de news literacy et de citoyenneté, laquelle est observée dans ses dimensions politique et numérique. Nos travaux démontrent que les compétences informationnelles nécessaires ou attendues pour participer à la vie démocratique se complexifient à la faveur d’un environnement médiatique et technologique en mutation rapide. Notre recension a permis de constater la richesse des travaux et des réflexions qui reflètent cette complexité des enjeux en cause. Il s’en dégage toutefois un flou conceptuel que l’article contribue à réduire.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".