Les dispositifs collaboratifs de confrontation et le rôle des interactions dans le contexte de l’analyse de pratique avec la vidéo
Bibliographic record
Abstract
La technologie vidéo est perçue comme un outil efficace pour favoriser une analyse réflexive de sa pratique. Cette revue de littérature répond à deux questions. Quels sont les types de confrontation vidéo qui favorisent l’analyse réflexive de sa pratique? Comment se déploient les interactions dans les dispositifs d’analyse de pratique collaboratifs avec la vidéo? À partir de notre corpus de 58 articles, nous présentons d’abord l’état actuel des connaissances concernant ces deux thèmes. Ensuite, à partir des conclusions qui ont émergé de notre revue de la littérature, nous tirons un ensemble de constat de recherche pour l’utilisation de la vidéo lors de l’analyse de sa pratique.
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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".