Spend Less, Get More? Explaining Health Spending and Outcome Differences Between Canada and Italy
Bibliographic record
Abstract
Canada spends more than Italy on health per capita and as a share of GDP and has a higher per capita GDP. Yet, life expectancy and infant mortality in Italy are better and have improved more over time. The implication is that the Italian health care system provides better value for money. We examine whether Italy does get better health outcomes at lower costs. Using regression analysis, we find that health spending is determined by similar drivers in both Canada and Italy. We also find that more social spending and health spending in either country do not satisfactorily explain the differences in health outcomes, suggesting the importance of broader socio-economic determinants like income and life-style choices. We conclude that while the levels of per capita health spending in Canada are higher than Italy, this partly reflects historical inertia in Canadian health spending partially attributable to the higher costs of health professionals relative to Italy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".