The Student Progress Committee: A Proactive Approach to Academic Excellence in an Age of Accountability
Bibliographic record
Abstract
INTRODUCTION Before 2001, responsibily for selecting students for admission to the College of Veterinary Medicine (CVM) at Washington State University (WSU) and for evaluating and addressing cases of veterinary student academic deficiency both lay with the admissions committee. To avoid the potential conflicts of interest that can arise in such a situation (e.g., a faculty member who had argued strongly for selecting a student for admission subsequently being asked to consider whether that student should be dismissed from the DVM program), an ad hoc committee was formed to explore ways in which admissions and academic standards functions could be handled by two mutually exclusive bodies in the college. An extensive investigation revealed that in many medical schools (e.g., University of Arizona, University of Washington, and Southern Illinois University), academic deficiencies are managed by Student Progress Committees (SPCs). The ad hoc committee proposed the formation of an SPC at WSU, and the Dean adopted this proposal as a solution to the problem of potentially conflicting roles for the CVM admissions committee.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".