Men’s Health Across the Lifespan: Health and Wellbeing of Older Male Prisoners
Bibliographic record
Abstract
Introduction: Older men aged 50 years and over are the fastest-growing cohort in the prisons of the United States (US) and the United Kingdom (UK). This reflects wider demographic change, such as increased life expectancy, as well as harsher sentencing policies, and an increased eagerness of courts to pursue historical offenses particularly relating to sexual crimes. Research has shown that older men in prison often experience poorer physical health than younger prisoners and those with similar age in the general public. However, to date, no such study has explored the health-related needs of older men held in Northern Ireland prisons. The aim of this research was to explore the health and wellbeing needs of older men held in custody in Northern Ireland. Method: A questionnaire was completed by 83 men aged 50 years or over, who were in prison in Northern Ireland in 2016. Comparisons were made with similar community-based surveys. Results: The data showed that on many indicators, older prisoners experience worse health than their peers living in the community. Conclusion: These findings suggest that there is a need for appropriate healthcare planning for older men in prison which recognizes how their health may differ from other age cohorts within prison, as well as from those living outside a custodial establishment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".