Homeless and incarcerated: An epidemiological study from Canada
Bibliographic record
Abstract
BACKGROUND: Incarceration and homelessness are closely related yet studied rarely. This article aimed to study the incarcerated homeless and identify specific vulnerabilities, which rendered them different from the nonincarcerated homeless. It also aimed to describe the homeless population and its significant involvement with the criminal justice and enforcement system. METHODS: Data were derived from the British Columbia Health of the Homeless Study (BCHOHS), carried out in three cities in British Columbia, Canada: the large urban center Vancouver (n = 250), Victoria (n = 150) and Prince George (n = 100). Measures included socio-demographic information, the Maudsley Addiction Profile (MAP), the Childhood Trauma Questionnaire (CTQ) and the Mini International Neuropsychiatric Interview (MINI) Plus. RESULTS: Incarcerated homeless were more often male (66.6%), were in foster care (56.4%) and had greater substance use especially of crack cocaine (69.6%) and crystal methamphetamine (78.7%). They also had greater scores on emotional and sexual abuse domains of CTQ, indicating greater abuse. A higher prevalence of depression (57%) and psychotic disorders (55.3%) was also observed. Risk factors identified which had a positive predictor value were male gender (p < .001; odds ratio (OR) = 2.8; 95% confidence interval (CI): 1.7-4.4), a diagnosis of depression (p = .02; 95% CI: 1.1-4.4) and severe emotional neglect (p = .02; 95% CI: 1.1-3.2) in the childhood. CONCLUSION: Homeless individuals may be traumatized at an early age, put into foster care, rendered homeless, initiated into substance use and re-traumatized on repeated occasions in adult life, rendering them vulnerable to incarceration and mental illness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".