Diabetes Portrayals in North American Print Media: A Qualitative and Quantitative Analysis
Bibliographic record
Abstract
OBJECTIVES: This study investigated how media coverage has portrayed diabetes as newsworthy. METHODS: The quantitative component involved tabulating diabetes coverage in 2 major Canadian newspapers, 1988-2001 and 1991-2001. The qualitative component focused on high-profile coverage in 2 major US magazines and 2 major Canadian newspapers, 1998-2000. RESULTS: Although coverage did not consistently increase, the quantitative results suggest an emphasis on linking diabetes with heart disease and mortality to convey its seriousness. The qualitative component identified 3 main ways of portraying type 2 diabetes: as an insidious problem, as a problem associated with particular populations, and as a medical problem. CONCLUSIONS: Overall, the results suggest that when communicating with journalists, researchers and advocates have stressed that diabetes maims and kills. Yet even when media coverage acknowledged societal forces and circumstances as causes, the proposed remedies did not always include or stress modifications to social contexts. Neither the societal causes of public health problems nor possible societal remedies automatically received attention from researchers or from journalists. Skilled advocacy is needed to put societal causes and solutions on public agendas.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".