Why are Women Canada's Fastest-Growing Prison Population and Why Should We Care?
Notice bibliographique
Résumé
When I first started work with Elizabeth Fry, I actually believed that there was not much difference between the circumstances of men and women prisoners. It only took a couple of months of being in the job to realize how wrong I was. Women's histories of neglect and abuse, poverty, motherhood, isolation and dislocation, and the overwhelming realization that they really were too often simply considered “too few to count” brought their circumstances into sharp relief, and I soon realized that the landscape of women's criminalization and imprisonment stood in stark contrast to any of my preconceived notions. The women and this work have educated and activated me in many ways, as we have journeyed many bumpy and seemingly obscure paths together. One such seemingly impassable journey and also one of life's turning points for me started on 28 April 1994, the day that I went into the Prison for Women (P4W) in Kingston aft er the emergency response team had stripped and shackled several women and left them naked or dressed with only a flimsy paper “gown” in the segregation unit. At the end of that long day, when I advocated that they unshackle the one woman who was still restrained and release from segregation all eight of the other women, I was advised that I was misinformed about the circumstances and treatment of the women and that, in fact, there were no women in restraints. When I insisted that I had actually observed the shackles, it was suggested by staff that perhaps it was a reflection from the bars. And when I persisted, I was counselled against being so easily “conned” by the women. As I exited P4W that evening with my then three-and-a-half-year-old son, I remember standing on the steps and realizing that they must believe that this information would never emerge and that if it did, no one would ever believe it. On that day, I thought, I don‘t know exactly how to do this, I don ‘ t know how one comes up against a system that has all of the resources and a full government department of lawyers to assist them in that process, but I had better figure out how.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,020 | 0,007 |
| Communication savante | 0,010 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».