Standing at the Intersection of Identity and Convict Criminology: A Brief Exercise in Reflexivity
Notice bibliographique
Résumé
The fi rst Convict Criminology (CC) session took place in 1997 at the American Society of Criminology's (ASC) annual meeting.The session was organized by members with personal experiences with the correctional system as formerly incarcerated (FI), as well as their allies.There was consensus among the group that many of the teachers in corrections had little, if any, experience in jails or prisons and lacked knowledge of what really took place behind their walls.In 2001, Richards and Ross defi ned the purpose and practice of CC, suggesting that those with fi rst-hand knowledge can provide an informed perspective on the functions and eff ects of prisons and jails.Merging insider knowledge, personal experience, and academic research related to criminal justice provides a paradigmatic approach that off ers distinct and relevant perspectives (Richards and Ross, 2001;Ross and Richards, 2003).In 2020, the Division of Convict Criminology (DCC) offi cially became part of the ASC.The original CC group was not particularly diverse, but over the last decade, the membership of CC has become more diverse in gender, sexuality, race and ethnicity, and FI background.The intersection of these identities among the members further increases the perspective and diversity of this group.As a CC member and the fi rst vice-chair of the DCC, supporting the mission and goals of the organization -including building diversity -are particularly important to me.Diverse experiences and voices support CC's mission to support justice-impacted scholars in providing rigorous research that examines all aspects of the criminal justice system, including policing, courts, and corrections, from those who have lived experiences within the fi eld (Tietjen, 2019).The DCC has explicitly addressed this issue, arguing that those in academia have largely ignored research from those who are formerly incarcerated or have had direct contact with the system.Acknowledging that the relevance of research conducted by incarcerated or FI individuals is often overlooked is signifi cant to the DCC's (2021) purpose: …to provide an intellectual home for all scholars/scientists who are interested in the study of Convict Criminology.The members of the
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».