The Association Between French Veterinary Practice Characteristics and Their Revenues and Veterinarian's Time Use
Bibliographic record
Abstract
The provision of healthcare by veterinarians consists of a blend of activities ensuring welfare for animals. It also contributes in the control of infectious diseases and food safety. In general practices, most of the activities generate incomes for veterinarians, notably acts (consultations, surgery, etc.) and sales (drugs, pet food, etc.). Increased size of veterinary practices and the arrival of corporate companies modify the veterinary landscape in many countries. In a context of rapid growth of the companion animal health market, the question of the profitability of veterinary activities is relevant. Indeed, beyond a certain threshold, veterinarians may be tempted to leave behind food-producing animals' acts and focus on companion animals' acts, which are generally recognized to be more profitable and more attractive for new generations of veterinarians. A survey was conducted in French veterinary mixed practices, and a regression analysis was used to quantify the relationships between the turnover and the characteristics of veterinary practices, the time to perform veterinary acts, and the characteristics of veterinarians. We found that the characteristics of veterinary practices are positively associated with the turnover and the price of acts, and that there was an association between the status of veterinarians (associate, collaborator, or employee) and the time required to perform companion animals' and food-producing animals' acts. The present study is the first study showing the association between the characteristics of veterinary practices and the turnover, by investigating the price of veterinary acts and the time required.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".