Comparison of Two Veterinary Emergency and Critical Care Clerkship Grading Protocols
Bibliographic record
Abstract
Universal guidelines for evaluating veterinary students' clinical clerkship performance are unavailable. At our institution, each service determines its own grading protocol. In this study, researchers compared clinician, staff, and student perceptions of a traditional and newly devised grading practice on the Emergency and Critical Care (ECC) clerkship. ECC clinicians and technicians were asked to assess the existing grading protocol for the clerkship. The system was then revised to better align with clerkship objectives. The revised protocol evaluated students on 12 items encompassing knowledge, clinical, and communication skills. Following the assignment of values for each category, letter grades were calculated automatically. Clinicians and staff were invited to rate the revised grading system. Throughout the study period, a corresponding survey was sent to students shortly after they had received their clerkship grades. Students' open-ended comments were analyzed qualitatively to identify common themes. Clinicians and technicians reported that the revised protocol was more inclusive and better able to provide fair and accurate assessments of students' performances. Students were generally satisfied with both grading protocols, however, in the open-ended comments students' frequently expressed desire for more directed and timely feedback on their performance. The results of this study indicate that the graders' believed that the revised evaluation protocol provides opportunities to provide fair and accurate assessments of student performance. Overall, students were satisfied with the new protocol and have a desire for tailored feedback provided in a timely fashion.
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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 | 0.091 | 0.248 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".