Evaluation and Comparison of Tolerance of Ambiguity in Veterinary Pathology Professionals and Trainees
Bibliographic record
Abstract
Ambiguity is ubiquitous in veterinary medicine, including in clinical and anatomic pathology. Tolerance of ambiguity (TOA) relates to how individuals navigate uncertainty. It is associated with psychological well-being in health professionals yet has been little investigated in veterinarians or veterinary pathologists. In this study, we used the Tolerance of Ambiguity of Veterinary Students (TAVS) scale and eight previously evaluated items specific to clinical pathology to evaluate and compare TOA in pathology professionals and trainees. We hypothesized that scores would be higher (reflecting greater TOA) for professionals than for trainees, that scores would increase with years of diagnostic experience for professionals and year of study for trainees, and that scores would be higher for clinical than anatomic pathologists due to the frequent ambiguity of clinical pathology practice. One hundred eighty one pathology professionals and trainees participated. TAVS scores were significantly higher for professionals than for trainees, and scores increased significantly with year of experience for professionals but not with year of study for trainees. When comparing disciplines, TAVS scores for all clinical pathologists were significantly lower than scores for all anatomic pathologists. Scores for clinical pathology-specific items showed similar trends to TAVS scores, except when comparing disciplines (clinical pathologists tended to have higher scores for these items). Results suggest pathology professionals become more tolerant of ambiguity throughout their careers, independent of increasing TOA with age, and that navigating ambiguity might be more difficult for trainees than for professionals. Educational interventions might help trainees learn to successfully navigate ambiguity, which could impact psychological well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".