Framing the issue of ageing and health care spending in Canada, the United Kingdom and the United States
Bibliographic record
Abstract
Political debates about the affordability of health care programmes in high-income countries often point to population ageing as a threat to sustainability. Debates in the United States, in particular, highlight concerns about intergenerational equity, whereby spending on older people is perceived as a threat to spending on the young. This paper compares how the problem of health spending is defined in Canada, the United Kingdom and the United States by presenting the results of a content analysis of print media during the period 2005-2010. We found that population ageing was cited as an important source of health care cost increases in all three countries but was cited less frequently in Canadian newspapers than in the UK or US papers. Direct claims about intergenerational equity are infrequent among the articles we coded, but newspaper articles in the United States were more likely than those in Canada and the United Kingdom to claim that of high health care spending on older people takes resources away from younger people. In Canada a much larger percentage of articles in our sample either claimed that high health care spending is crowding out other types of government expenditure. Finally, we found that almost no articles in the United States challenged the view that population ageing causes health care spending, whereas in both Canada and the United Kingdom a small, but steady stream of articles challenged the idea that population ageing is to blame for health care spending increases.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.020 | 0.030 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".