Cyborg : approche anthropologique de l’hybridité corporelle bio-mécanique
Bibliographic record
Abstract
Lorsqu’on s’intéresse à la question de l’hybridité, en particulier corporelle, l’image du cyborg est incontournable. Cette figure de la science-fiction nous invite à interroger les complexes liens qui unissent le corps et la machine. Dans cette rencontre du mécanique et du biologique, il est à la fois un symbole d’une redéfinition de la vie humaine et une cristallisation de fascination ou de répulsion. Partant des exemples proposés par le cinéma d’animation japonais, cet article vise à dégager différentes thématiques de l’hybridité, différents aspects de ces expériences fictives. Créature de simulacre, être de monstruosité, produit surpuissant d’un dérèglement social et scientifique, chose informe débordant d’une identité close et unifiée, les images du cyborg révèlent sa grande labilité métaphorique. Plus qu’une simple forme émergeant de constructions fabuleuses, il nous parle aussi du sens que les sociétés modernes attribuent au corps technicisé.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".