Banditisme social, m~~moire collective et histoire : le r~~le de Jesse James dans la cr~~ation de sa propre l~~gende
Bibliographic record
Abstract
En 1939, le film Jesse James, dans lequel Tyrone Power incarne le c~~l~~- bre hors-la-loi, connaissait un succ~~s foudroyant au box-office1. Dans ce film, Henry King, r~~alisateur, repr~~sente Jesse James comme un jeune homme s'~~tant tourn~~ vers le crime pour venger le meurtre de sa m~~re commis par des agents de compagnies ferroviaires. Aid~~ par son fr~~re Frank (Henry Fonda), Jesse se venge et s'attaque ~~ la corruption engendr~~e par le progr~~s dont le train est la repr~~senta- tion la plus n~~faste. Cependant, le banditisme de Jesse devient avec le temps une activit~~ pratiqu~~e pour le profit plut~~t que pour le bien de la communaut~~. Notamment, King d~~montre cette transition par un changement d'attitude de Jesse quand au commandement de sa bande (la bande James-Younger), passant de leader ~~ ~~ dictateur ~~. Lorsque qu'il affirme ~~ son fr~~re qu'il peut gravir les marches du Capitole s'il le d~~sire, ce dernier le replace juste ~~ temps dans le droit chemin. Malgr~~ le retour au banditisme social, la bande est d~~faite ~~ Northfield. Jesse est subs~~quemment tu~~ par Robert Ford alors qu'il vient de promettre ~~ son ~~pouse qu'il va se ranger.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".