An examination of psycho-social conditions under which provincially sentenced women offend
Bibliographic record
Abstract
Findings from this study support previous research that emphasizes the need for a gender responsive framework in understanding women's offending as well as the importance of examining 'dynamic' factors in women's offending. Results point to the role of victimization, substance abuse, poverty, marginalization and its long-term impact on mental health and women's capacity for survival. Implications for women's abilities to overcome these barriers in their successful re-integration into the community are discussed as well as the need for addressing these issues in designing correctional programs and policy. This study investigated psychological and social conditions under which provincially sentenced women offend. It examined women's present day life circumstances (i.e. economic disadvantage, current addictions, adult victimization, employment, and unstable housing and social support), psychological functioning (i.e. coping styles, self-efficacy, attributional style, mental distress), attitude to crime, historical factors (criminal history, childhood victimization) and their influence on women's offending. Findings demonstrated that women offenders were doing significantly worse on various aspects of psychological functioning and mental health compared to women in the general population and recidivists were experiencing significantly greater problems in areas of social support, adult victimization, addictions and poverty than first time offenders. Overall, women offenders did not appear to demonstrate procriminal attitudes, however, significantly more recidivists had histories of juvenile offending, problem avoidance styles as well as slightly more procriminal attitudes than first time offenders. 'Higher rate' offenders demonstrated significantly more problems with current addictions, unemployment, poverty and histories of juvenile offending. Psychological functioning, difficult life circumstances and experiences of historical disadvantage were factors that explained higher rates of offending in the group of 'higher rate' offenders. Experiences of historical disadvantage and difficult life circumstances explained diverse aspects of psychological functioning including low self-efficacy, use of problem avoidance as a coping style, mental distress and pessimistic attributional style. Results also demonstrated that for recidivists poverty was a salient factor in re-offending.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".