Veterinary Students as Elite Performers: Preliminary Insights
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The KPMG ''Mega Study'' (Brown JP, Silverman JD. The current and future market for veterinarians and veterinary medical services in the United States. J Am Vet Med Assoc 215:161-183, 1999) and other studies (Cron WL, Slocum JV, Goodnight DB, Volk JO. Impact of management practices and business behaviors on small animal veterinarians' incomes. J Am Vet Med Assoc 217:332-338, 1999; Lewis RE. Non-technical Competencies Underlying Career Success as a Veterinarian: A New Model for Selecting and Training Veterinary Students. Minneapolis: Personnel Decisions, 2002) concur that improvement in veterinary practitioner performance is necessary. Improvement in practitioners' non-technical competencies is considered most vital. Little research exists that identifies underlying psychological factors harbored by veterinary students that inhibit ability to achieve sustained maximum professional performance. Left unaddressed, these same characteristics may lead to coping behaviors that disrupt or, in the worst cases, lead to voluntary or involuntary termination of professional careers. Several performance-related characteristics and interpersonal dynamics are investigated in this study that provide preliminary evidence for the long-term shortcomings addressed in previous veterinary practice management literature. Pedagogical recommendations for addressing these student psychological characteristics are submitted for consideration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it