Le judiciaire, la détermination de la peine et la polycontexturalité de l’opinion publique
Bibliographic record
Abstract
Résumé Cet article propose de re-conceptualiser la manière dont les sciences sociales et juridiques se sont traditionnellement représenté le rapport du système judiciaire à l’opinion publique. Nos développements s’appuient sur la théorie des systèmes de Niklas Luhmann de même que sur des exemples empiriques tirés de la jurisprudence et d’entretiens qualitatifs permettant de mettre en évidence le potentiel heuristique d’une polycontexturalisation de l’opinion publique. En sciences sociales et juridiques, si les recherches se sont surtout intéressées au point de vue de l’opinion publique sur la justice du judiciaire, la notion de polycontexturalité nous amène, quant à elle, à déplacer l’angle d’observation et à privilégier l’analyse des structures impliquées dans la sélection et la mise en forme judiciaire des opinions publiques privilégiées. L’objectif n’est alors plus celui de comprendre comment l’opinion publique pense le judiciaire, mais plutôt de comprendre à cet égard comment le judiciaire pense que l’opinion publique pense.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.038 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".