Fee Increases and Target Income Hypothesis: Data from Quebec on Physicians’ Compensation and Service Volumes
Bibliographic record
Abstract
Recent years have witnessed important public investments in physicians' compensation across Canada.The current paper uses data from Quebec to assess the impact of those investments on the volumes of services provided to the population.While total physician compensation costs, average physician compensation and average unit cost per service all rose extremely fast, the total number of services, number of services per capita and average number of services per physician either stagnated or declined.This pattern is compatible with the economic target income hypothesis and raises important policy questions. RésuméCes dernières années, d'importants investissements publics dans la rémunération des médecins ont été consentis partout au Canada.Cet article utilise les données du Québec pour évaluer l'impact de ces investissements sur le volume de services fourni à la population.Alors que les dépenses totales liées à la rémunération des médecins, la rémunération moyenne par médecin
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".