Les réincarcérations multiples : profil sexué d’un groupe de justiciables
Bibliographic record
Abstract
Women offenders had traditionally been neglected in criminological theory as well as in empirical analyses. Feminist studies have shown that such an exclusion was not only inacceptable on a political ground but that it also shed serious doubts about the validity of criminological models. Arguing on the necessity of focussed empirical analyses for a better understanding of the dynamics of sexual identity on the nature of penal interventions, the authors have proceeded to a comparative analysis of the characteristics and penal treatment of a particular group of offenders, those that have been incarcerated in Quebec's provincial jails ten times or more during a ten year period. Results stress the complexity of the différenciation process for women and men, at least for this particular group. Women having been through repeated incarcerations are far less numerous than men. But the motives for which these women were imprisoned appear to be even more trivial than those having prompted the men's incarcerations.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".