Universal Health Insurance and Health Care Access for Homeless Persons
Bibliographic record
Abstract
OBJECTIVES: We examined the extent of unmet needs and barriers to accessing health care among homeless people within a universal health insurance system. METHODS: We randomly selected a representative sample of 1169 homeless individuals at shelters and meal programs in Toronto, Ontario. We determined the prevalence of self-reported unmet needs for health care in the past 12 months and used regression analyses to identify factors associated with unmet needs. RESULTS: Unmet health care needs were reported by 17% of participants. Compared with Toronto's general population, unmet needs were significantly more common among homeless individuals, particularly among homeless women with dependent children. Factors independently associated with a greater likelihood of unmet needs were younger age, having been a victim of physical assault in the past 12 months, and lower mental and physical health scores on the 12-Item Short Form Health Survey. CONCLUSIONS: Within a system of universal health insurance, homeless people still encounter barriers to obtaining health care. Strategies to reduce nonfinancial barriers faced by homeless women with children, younger adults, and recent victims of physical assault should be explored.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".