Espaces et lieux d’humanisation : quel statut accorder aux productions techno-scientifiques?
Bibliographic record
Abstract
La multiplication des innovations techno-scientifiques marque de façon toute particulière le monde contemporain. Quel statut doit-on leur accorder? L’espace actuel de la réflexion critique ne les rend-il pas d’emblée suspectes, sujettes à condamnation, coupables d’une perte de lien social et d’humanité? Axées sur l’efficacité, porteuses d’uniformisation et de contraintes à l’expression du subjectif, ces innovations ne sont-elles pas, parnature, déshumanisantes? Dans cet article, l’auteure tente d’ouvrir d’autres espaces de réflexion pour penser les techno-sciences et la façon dont elles interviennent dans le débat sur la déshumanisation et la réhumanisation. Tirant profit d’une recherche à travers laquelle elle a suivi le travail d’invention d’une nouvelle méthode contraceptive, l’auteure fait valoir la portée, mais aussi les difficultés, d’une démarche qui met en doute les frontières apparemment hermétiques et infranchissables entre ce qui relève du monde des choses et ce qui relève de l’humain.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.082 |
| Scholarly communication | 0.022 | 0.021 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 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".