Comprendre les expériences de violences et de recours d’aide des femmes Mi’gmaq : résultats qualitatifs et appliqués d’une étude partenariale dans la communauté de Listuguj [synthèse en français]
Bibliographic record
Abstract
Il s’agit de la synthèse en français de l’article "Understanding the violence and help-seeking experiences of Mi’gmaq women: Qualitative and applied results from a partnered study in the community of Listuguj" paru dans le même numéro d’Alterstice. Émergeant d’une étude partenariale au sein de la communauté Mi’gmaq de Listuguj, cet article a été rédigé en anglais par souci d’inclusion des partenaires dans le processus d’écriture et de diffusion auprès de la communauté. L’objectif était de comprendre les expériences de violences et de recours d’aide des femmes Mi’gmaq afin de développer des solutions pour améliorer les services offerts dans la communauté. Cette étude partenariale est importante, non seulement car elle réaffirme l’interrelation entre les violences interpersonnelles et les violences structurelles dans la vie des femmes autochtones, mais aussi car ses résultats appliqués peuvent être utilisés par la communauté de Listuguj pour mieux répondre aux besoins des survivantes de violences.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".