The Classification of Federally Sentenced Women in Canada: Addition of Gender-Informed Variables to the Custody Rating Scale Contributes Incremental Predictive Validity
The Correctional Service of Canada (CSC) uses the Custody Rating Scale (CRS) for initial security classification; it is gender-neutral. Gender-informed scholars contend that gender-neutral assessments are problematic for use with justice-impacted women, as they exclude factors (e.g., victimization)...
| Autores principales: | ; ; |
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| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| En: |
Criminal justice and behavior
Año: 2023, Volumen: 50, Número: 12, Páginas: 1759-1782 |
| Acceso en línea: |
Volltext (kostenfrei) |
| Journals Online & Print: | |
| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | The Correctional Service of Canada (CSC) uses the Custody Rating Scale (CRS) for initial security classification; it is gender-neutral. Gender-informed scholars contend that gender-neutral assessments are problematic for use with justice-impacted women, as they exclude factors (e.g., victimization) deemed more relevant for women. Using an archival database with 1,555 federally sentenced women in Canada, we examined the extent that gender-informed indicators could yield incremental predictive validity (predicting institutional misconduct) beyond the CRS. Specifically, gender-informed variables from these domains were tested: mental health, substance misuse, relationship dysfunction, personal/emotional difficulties, parental/family issues, and victimization. Results revealed at least one gender-informed variable from each domain significantly predicted institutional misconducts. Composite gender-informed scales were created from the set of significant gender-informed predictors. Area under the curve (AUC) and hierarchical Cox regression analyses revealed the composite gender-informed scales contributed incremental predictive validity above and beyond the CRS. Although the CRS was predictive, it can be improved by including gender-informed variables. |
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| ISSN: | 1552-3594 |
| DOI: | 10.1177/00938548231202799 |
