Urban Aboriginal Health Counts: Barriers to Access to Health Services and Their Relationship With Cardiovascular Disease and Hypertension in an Urban First Nations Population
Bibliographic record
Abstract
Background: Hypertension and cardiovascular disease (CVD) contribute to morbidity and mortality among First Nations peoples. Despite increased urbanization of this group, there is little data on the health of this community in an urban environment. \n \nObjective: To examine the association between barriers to access to health services and the prevalence of hypertension and CVD in an urban First Nations population. \n \nMethods: Data were obtained from the Our Health Counts survey, which used Respondent-Driven Sampling, a chain-referral sampling technique. Analysis was done using newly proposed, modified multivariable logistic regression models. \n \nResults: The prevalence of hypertension in this urban First Nations population was associated with poor access to both traditional and conventional health services. CVD was associated with housing conditions and poor diet. \n \nConclusion: Given the importance of access to conventional and traditional care, and housing variables, a holistic, culturally appropriate perspective may be important for maintaining cardiac health in this community.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".