The Health Buck Stops Where? Thematic Framing of Health Discourse to Understand the Context for CVD Prevention
Bibliographic record
Abstract
Using a constructed week methodology, we analyzed media summaries for the type of health discourse (health care delivery, disease-specific prevention, lifestyle risk factors, public/environmental health disease, social determinants of health) portrayed over a 5-year period as a means of describing the context within which health staff worked to prevent heart disease in one Canadian province. The results reveal that heart disease received very little media coverage, despite provincial health data revealing it to be the leading cause of mortality, morbidity, and health care costs. Coverage of the health care system dominated the media landscape over the 5-year period. The study findings also suggest that the health discourses in the media summaries were represented as primarily thematic, rather than as episodic narratives, relieving any one level of government as entirely responsible for the health of its constituents. Media advocacy strategies may be a means to redress the imbalance of health discourses presented by the media.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".