“Do You Want to Go Forward or Do You Want to Go Under?” Men’s Mental Health in and Out of Prison
Bibliographic record
Abstract
More than 11 million people are currently imprisoned worldwide, with the vast majority of incarcerated individuals being male. Hypermasculine environments in prison are often tied to men's health risks, and gathering information about mental health is fundamental to improving prison as well as community services. The purpose of the current study was to describe the connections between masculinities and men's mental health among prisoners transitioning into and out of a Canadian federal correctional facility. Two focus groups were conducted with a total of 18 men who had recently been released from a federal correctional facility. The focus group interviews were analyzed to inductively derive patterns pertaining to men's mental health challenges and resiliencies "on the inside" and "on the outside." Participant's challenges in prison related to heightened stresses associated with being incarcerated and the negative impact on preexisting mental illness including imposed changes to treatment regimens. Men's resiliencies included relinquishing aggression and connecting to learn from other men "on the inside." Mental health challenges "on the outside" included a lack of work skills and finances which increased the barriers that many men experienced when trying to access community-based mental health services. Mental health resiliencies employed by participants "on the outside" included self-monitoring and management to reduce negative thoughts, avoiding substance use and attaining adequate exercise and sleep. The current study findings offer practice and policy guidance to advance the well-being of this vulnerable subgroup of men in as well as out of prison.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".