Gestures, facial expressions and words for talking, learning and understanding
Bibliographic record
Abstract
Resume La multimodalite de la communication renvoie aux differentes modalites expressives et non-verbales qui permettent de communiquer avec autrui ; ainsi, gestes de la main et de la tete, mimiques faciales et regards completent et/ou nuancent le message verbal. L’idee de considerer que le developpement de la communication est multimodal est recente ; en effet, les progres technologiques mais aussi une facon differente d’envisager des modeles relatifs au developpement ou au fonctionnement de l’adulte ont permis de faire emerger de nouvelles questions de recherche et de nouveaux faits. Ainsi, les travaux realises au cours des vingt dernieres annees montrent que la prise en compte de la multimodalite permet d’accroitre nos connaissances non seulement a propos du developpement de la communication et du langage mais aussi a propos des mecanismes d’apprentissage sur autrui et sur le monde.L’objectif de ce numero thematique d’Enfance est de presenter des travaux realises par des specialistes au plan international du domaine en provenance tant d’Europe francophone et anglophone que des Etats-Unis et du Canada. Les recherches presentees portent a la fois sur le developpement typique et atypique et ont des retombees a la fois en termes de recherche fondamentale pour mieux comprendre le developpement tant normal que trouble mais aussi en termes plus appliques pour esquisser des pistes tant au niveau de l’evaluation que de la prise en charge des enfants avec troubles et handicaps du developpement.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".