Veterinary Medicine and the Lifeboat Test: A Perspective on the Social Relevance of the Veterinary Profession in the Twenty–First Century
Bibliographic record
Abstract
Over the past several decades, the veterinary profession in North America has become severely imbalanced and now serves society in a very lopsided way. What we do, we do very well. But what we do not do, or do too little, is a shameful disservice to society. What do veterinarians do? In North America in 2004, veterinarians do clinical practice, especially companion animal practice, and not much else. No detailed statistics on veterinary activity in Canada appear to exist, but Canadian statistics probably are very similar to those available for the United States. According to the American Veterinary Medical Association, in 2002, 90% of all veterinarians were in clinical practice, and 75 % to 80% of practitioner time, or about 70% of total veterinary activity, was devoted to companion animals, mostly dogs, cats, and horses (American Veterinary Medical Association, 2003).
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".