International Comparisons of Manpower in Gastroenterology
Bibliographic record
Abstract
Health-care systems vary among countries and we were interested in how this might impact on gastroenterology manpower. We assessed the number of gastroenterologists in Canada and compared this with four countries where data were available over the Internet in either French or English. The number of gastroenterologists per 100,000 of the population was 3.9 in the United States, 3.48 in France, 2.1 in Australia, 1.83 in Canada, and 1.41 in the U.K. This variation in number of gastroenterologists was not reflected in the overall number of specialists per 100,000, which was similar in all five countries. Furthermore, the difference in gastroenterology manpower did not correlate with the amount of gross domestic product spent on health care. Countries with a low number of gastroenterologists per 100,000 all had a strong primary-care gatekeeper system, although this observation may be coincidental, as only five countries were studied. Canada had the most equitable distribution of gastroenterologists across the country with only modest differences among provinces. The United States had the most variation in the number of gastroenterologists per 100,000 of the population among states.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".