Challenges and Issues Surrounding Promotion and Tenure of Faculty with Clinical Service Responsibilities in Veterinary Medicine
Bibliographic record
Abstract
Mentoring, assessing, and rewarding faculty who have clinical service responsibilities with promotion and tenure can be challenging in many respects. Clinical service responsibilities can limit the time that faculty have available to participate in scholarly activities, especially if the scholarship required for promotion is restricted to traditional research efforts where an individual faculty member is assessed in terms of the number of scientific publications in high-tiered journals with senior authorship and the amount of extramural funding garnered. Even if other forms of scholarship are recognized, metrics used to evaluate research efforts are often inappropriately applied to other scholarly activities. This challenge is not unique to veterinary medicine. This literature review reveals information regarding barriers and recommended solutions from other healthcare and service professions as recognizing scholarly engagement in academic veterinary medicine is just beginning. Opportunities and examples of how faculty can derive scholarship from their clinical service activities are provided. In addition, an approach for mentoring faculty in the prospective planning and documenting of scholarly engagement efforts is suggested. Lastly, challenges and guidance for assessing such scholarship in academic veterinary medicine are recommended as one step toward encouraging colleges of veterinary medicine to develop methods to assess scholarly engagement within their promotion and tenure processes. A change in approach to the promotion and tenure process can result in more faculty being rewarded for their clinical, diagnostic, and scholarly excellence, which positively impacts patient care, career fulfillment, institutional reputation, the veterinary profession, and society as a whole.
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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 | 0.117 | 0.209 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.026 | 0.018 |
| Open science | 0.006 | 0.017 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".