Context and Cardiovascular Risk Modification in Two Regions of Ontario, Canada: A Photo Elicitation Study
Bibliographic record
Abstract
Cardiovascular diseases, which include coronary heart diseases (CHD), remain the leading cause of death in Canada and other industrialized countries. This qualitative study used photo-elicitation, focus groups and in-depth interviews to understand health behaviour change from the perspectives of 38 people who were aware of their high risk for CHD and had received information about cardiovascular risk modification while participating in a larger intervention study. Participants were drawn from two selected regions: Sudbury and District (northern Ontario) and the Greater Toronto Area (southern Ontario). Analysis drew on concepts of place and space to capture the complex interplay between geographic location, sociodemographic position, and people's efforts to understand and modify their risk for CHD. Three major sites of difference and ambiguity emerged: 1) place and access to health resources; 2) time and food culture; and 3) itineraries or travels through multiple locations. All participants reported difficulties in learning and adhering to new lifestyle patterns, but access to supportive health resources was different in the two regions. Even within regions, subgroups experienced different patterns of constraint and advantage. In each region, "fast" food and traditional foods were entrenched within different temporal and social meanings. Finally, different and shifting strategies for risk modification were required at various points during daily and seasonal travels through neighbourhoods, to workplaces, or on vacation. Thus health education for CHD risk modification should be place-specific and tailored to the needs and resources of specific communities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".