L’engagement du corps : un enjeu dans le pilotage en ligne d’un avion à cockpit de verre (glass-cockpit)
Bibliographic record
Abstract
La mise en place d’une nouvelle génération d’avions de ligne (glass-cockpit) au début des années 90 a fait l’objet de vives controverses. Un des enjeux essentiels du débat qui s’est instauré alors autour des glass-cockpits s’est ancré sur la question des sens et plus précisément du retour sensoriel des informations dont les pilotes se sentaient privés. On a vu ainsi émerger explicitement autour de cette question de l’usage que les pilotes font de leur corps et de leurs sens un motif de tension entre une automatisation qui tend à mettre le corps à distance et une appropriation qui utilise le corps comme un des moteurs principaux de sa mise en œuvre. Cet article rend compte, à partir de l’expérience des pilotes, de la manière dont le mode de présence du corps, ou sa négation, participe de la définition et du rôle de l’humain dans un environnement automatisé.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".