EDUCATION, LICENSING, AND THE EXPANDING SCOPE OF VETERINARY PRACTICE MEMBERS EXPRESS THEIR VIEWS
Bibliographic record
Abstract
Once again, members of the Canadian Veterinary Medical Association (CVMA) spoke out on one of the major challenges facing the veterinary profession: “Is there a problem with the competency of new graduates to address the rising tide of societal expectations and needs served by the veterinary profession?” Judging by the overwhelming response to a recent survey and the feedback provided by participants, one thing is clear ... the educational and licensing system is important to CVMA members, and this issue has prompted considerable discussions, varied opinions, and compelling arguments. The CVMA's member opinion survey mailed with the November and December 2002 issues of The Canadian Veterinary Journal (CVJ) generated over 800 responses, which represents a 17% rate of return. Members were initially invited to read the background report of the CVMA Task Force on Education, Licensing, and the Expanding Scope of Veterinary Practice that appeared in the same issues of the CVJ. This report summarizes the arguments for and against graduating veterinarians with in-depth training focused on major fields of veterinary medicine, and analyzes its effect on veterinary education and how the veterinary licensing system might respond at the national and provincial levels. It also addresses the issues of maintaining and enhancing diversity in the profession. Readers were then asked to respond to the following questions: How serious is the problem of lack of competence and/or confidence of veterinary graduates in addressing the existing needs of the groups we serve? If you are of the opinion that there is a serious problem, in what single practice type is it a problem? In addressing the problems identified by the Task Force, and in light of the Summit participants' opinions, choose your single preferred solution.†
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.013 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".