GESTES POUR ÉCRIRE ET LIRE À L’HEURE DES APPAREILS NUMÉRIQUES
Bibliographic record
Abstract
Les écrans et claviers tactiles utilisés par les enfants et les adolescents font émerger de nouveaux gestes d’écriture et de lecture, qui semblent modifier les habitudes acquises par chacun lors de l’apprentissage du lire/écrire. Le but de cet essai est de penser à ces nouveaux gestes de trois points de vue. La première partie de la réflexion se base sur les travaux anthropologiques de Leroi-Gourhan (2008a, 2008b), mettant en évidence la relation évolutive entre les supports, les gestes, le temps et les espaces culturels. La deuxième partie analyse les recommandations ministérielles françaises — de 2006, 2011 et 2015 — concernant l’enseignement des gestes d’écriture. La troisième partie prend appui sur les travaux de Bouchardon (2011) pour analyser les gestes émergents créés par les lecteurs sur support numérique. Les résultats mettent en évidence la nécessité d’intégrer des gestes émergents dans la culture de l’école comme moyen de valoriser la diversité des gestes, des outils et des supports de lecture et d’écriture.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 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".