The Complex Role of Veterinary Clinical Teachers: How Is Their Role Perceived and What Is Expected of Them?
Bibliographic record
Abstract
The purpose of this study was to identify personal attributes in veterinary clinical teachers that are valued most by members of their work environment (fellow faculty, clinical training scholars [CTS; residents], undergraduate students, and referring veterinary surgeons) and to determine whether the opinions of these subgroups differed. Faculty (n=50), CTS (n=35), students (n=200), and referring veterinary surgeons (n=25) were presented with a list of 15 potentially desirable attributes. Respondents were asked to rank the three most important and the three least important attributes of effective clinical teachers. Respondents were also asked to select in which of the three main activities (clinical service, teaching, or research) in which clinical teachers currently invest the most and the least effort and in which they should invest the most and the least effort. All respondent groups agreed that "competence-knowledge" was among the most desirable attributes. Faculty, undergraduate students, and referring veterinary surgeons additionally included "enthusiasm" in the top three, whereas CTS regarded "respects independence" as more important. All respondent groups consistently chose "scholarly activity" as one of the three least important characteristics. A similar number of faculty members (38%) expressed that the greatest effort should be invested in clinical service or teaching, and the greatest proportions of CTS (44%) and students (56%) felt that most emphasis should be put on teaching alone. The differences in opinion between respondent groups regarding importance of attributes and emphasis of activity indicate that what is perceived as effective performance of clinical teachers differs depending on the role of those who engage with them.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".