Mental health needs of federal female offenders.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mental health problems are increasingly being recognized as one of the greatest challenges faced by correctional systems in the effective management of their populations. Over the past decade, the number of federally sentenced female offenders in Canada presenting with mental health problems has risen significantly, from 13% in 1996/1997 to 29% in 2008/2009 (Correctional Service of Canada, 2009a). This research used the screener version of the Computerized Diagnostic Interview Schedule (C-DIS-IV; n = 88) to outline the mental health needs of federally sentenced females in Canada. Results provide evidence for extremely elevated rates for certain diagnoses and confirm substance dependence as a significant area of need in this sample. Moreover, alcohol dependence emerged as an area of particular concern for Aboriginal women. Furthermore, all individuals experiencing a lifetime substance dependence disorder have also suffered from an additional psychiatric diagnosis at some point in their lives; thereby highlighting the possible levels of concurrent disorders among this population. This research highlights the critical importance of comprehensive and ongoing mental health assessment, and treatment, for the successful management and reintegration of female offenders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 it