Les natifs numériques profitent-ils de la convergence ? Constats nuancés et pistes de réflexion pour les éducateurs
Bibliographic record
Abstract
L’enthousiasme ou la défiance vis-à-vis de la culture de la convergence et des natifs numériques peuvent aujourd’hui être discutés à la lumière de recherches sur les pratiques effectives des utilisateurs. Cet article fondé sur deux terrains complémentaires (un projet scientifique et un projet pédagogique) menés par deux équipes de recherche, examine l’usage des médias sociaux chez de jeunes français. En étudiant trois enjeux centraux : l’évaluation de l’information, le management de son identité numérique et le temps de connexion, l’analyse révèle une certaine facilité d’accès mais aussi de plus grands défis en termes de compétences. Des pistes de réflexion pour une éducation aux médias sociaux sont esquissées dans la dernière partie.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".