Mass print media depictions of cancer and heart disease: community versus individualistic perspectives?
Bibliographic record
Abstract
This paper is based on a critical discourse content analysis of 40 stories from the 20 highest circulating English-language mass magazines available in Canada and published in Canada or the USA in 2001. It examines the presence or absence of the social determinants perspective in the portrayal of the two most significant causes of morbidity and mortality in these countries: cancer and heart disease. The media analysis documents an absence of reflection of the social determinants viewpoint on these, the most important causes of disease and death. Thus, magazine stories ignore the role of such considerations as income, education level, ethnicity, visible minority or, Aboriginal status, early life experiences, employment and working conditions, food accessibility and quality, housing, social services, social exclusion, or unemployment and employment security in explaining health. Instead, the magazine articles underscore an individualistic approach to disease that assumes that health care is accessible and available to all, and that these diseases are preventable and treatable through individual lifestyle choices in combination with the measures prescribed through conventional medicine. Although cancer and heart disease are framed by a medical discourse, articles tended to emphasise the independence, freedom and power of the individual within the medical care system. The research documents a continuation of the dominance of conventional medicine buttressed by individualism in media stories. Theoretical and methodological issues are discussed. Some of the practical consequences for policy-makers and professionals are noted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| 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".