Saltations 1999. Greg Bear, Greg Egan, David Cronenberg et le mutant « évolutif »
Bibliographic record
Abstract
L’année 1999 marque le retour en grâce du mutant dans la science-fiction « sérieuse ». Avec les romans Darwin’s Radio de Greg Bear et Teranesia de Greg Egan, ce sont deux maîtres de la hard science fiction qui revisitent coup sur coup le thème de l’épidémie mutagène à l’aune des transformations récentes de la biologie et notamment de la théorie de l’évolution. Pour Gérard Klein, ces deux écrivains auraient acté la mise en cause du « gradualisme » darwinien, et le retour du mutant de SF accompagnerait logiquement celui des hypothèses « saltationnistes ». Or une comparaison s’impose avec le film Crimes of the Future (2022) de David Cronenberg, une histoire d’« évolution accélérée » dont l’écriture remonte précisément à la toute fin des années 1990. Il y a bien eu une discussion entre science-fiction et darwinisme au tournant du millénaire, mais elle a dépassé les limites et les limitations du biotech thriller .
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".