Usages prescrits et figure de l’utilisateur modèle dans le design du web-documentaire B4, fenêtres sur tour
Bibliographic record
Abstract
Le présent article interroge la manière dont l’ensemble des professionnels impliqués dans le design d’un documentaire interactif anticipent et négocient les usages d’un « spectateur-actant ». L’auteur a mené une observation participante pendant les six mois de conception du web-documentaire B4, fenêtres sur tour, coproduit par Mosaïque films et France Télévisions Nouvelles Écritures. La grille d’analyse adoptée met en évidence l’ensemble des controverses sociotechniques et sémio-pragmatiques qui préfigurent l’œuvre en devenir. Une figure tridimensionnelle de l’utilisateur modèle est ainsi modélisée. Les dimensions exogène, interactionnelle et capacitationnelle de cet utilisateur modèle permettent in fine de tirer un enseignement méthodologique sur le design de ce format émergent et non stabilisé.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".