Impostor phenomenon in veterinary medicine
Bibliographic record
Abstract
Background: Impostor phenomenon (IP), an internal perception of intellectual phoniness despite personal achievements, has been reported and evaluated in a number of professions, including doctors, dentists, pharmacists, and academic faculty. To date, this phenomenon has not been evaluated in the veterinary medicine. Methods: To examine the prevalence of IP in veterinary medicine, we surveyed veterinary students, house officers, and veterinarians at a large college of veterinary medicine. Survey measures included the Clance IP Scale (CIPS) and Young Impostor Scale (YIS). Results: The prevalence of IP in our population was 50%, 68%, and 34%, among students, house officers, and faculty, respectively, based on the responses to the CIPS. The prevalence of IP was 45%, 60%, and 26%, among students, house officers, and faculty, respectively, based on the responses to the YIS. Conclusion: Among veterinary students, house officers and faculty IP are experienced to a similar degree as that reported in other health professions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".