The (Paper)Work of Medicine: Understanding International Medical Costs
Bibliographic record
Abstract
This paper draws on international evidence on medical spending to examine what the United States can learn about making its healthcare system more efficient. We focus primarily on understanding contemporaneous differences in the level of spending, generally from the 2000s. Medical spending differs across countries either because the price of services differs (for example, a coronary bypass surgery operation may cost more in the United States than in other countries) or because people receive more services in some countries than in others (for example, more bypass surgery operations). Within the price category, there are two further issues: whether factors earn different returns across countries and whether more clinical or administrative personnel are required to deliver the same care in different countries. We first present the results of a decomposition of healthcare spending along these lines in the United States and in Canada. We then delve into each component in more detail—administrative costs, factor prices, and the provision of care received—bringing in a broader range of international evidence when possible. Finally, we touch upon the organization of primary and chronic disease care and discuss possible gains in that area.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".