They Are Not My Problem: A Content and Framing Analysis of References to the Social Determinants of Health within Canadian News Media, 1993–2014
Bibliographic record
Abstract
As public support is essential for implementing policies that act on the underlying social determinants of health (SDOH), it is important to consider how the public is exposed to this issue. This article explores how the SDOH have been represented in Canadian news media articles from 1993 to 2014. Of the 113 articles that explicitly included SDOH, housing (12.9%), income (10.5%), and poverty (9.3%) were most frequently reported. Over time, the reporting of SDOH increased, with peaks of coverage occurring at different times for different determinants (e.g., housing in 2005, income in 2009). A framing analysis revealed that the SDOH are presented in multiple ways: as an actionable issue and responsibility of government, a moral responsibility, and—problematically—as an issue that only affects disadvantaged groups.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.020 | 0.023 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.010 | 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".