Using Standardized Essays in the Veterinary Medicine Admissions Process: Are the Ratings Reliable and Valid?
Bibliographic record
Abstract
The reliability and validity of using essays for veterinary medical school admissions requires investigation. We explored the reliability and construct validity of a structured essay station in the 2009 admission process at the University of Calgary Faculty of Veterinary Medicine. One hundred three applicants (female=80.6%, male=19.4%; mean age=23.05 years, SD=3.96) participated. Each applicant wrote a one-hour supervised essay (750 words). Essays were rated independently by two randomly assigned raters (n=16). Raters scored essays on four items, each on a five-point anchored scale. Nine essays were scored by all raters to perform a decision study. Generalizability analysis resulted in a reliability coefficient of 0.55. The decision study indicated that three raters and four items produces a G of 0.68. Essay score correlated with interview score (r=0.30, p<0.01) but not with GPA (r=0.05, p=ns). Overall reliability was adequate and higher than what has been reported for unsupervised written submissions. Results from the decision study suggest that three raters with four items provide adequate reliability. Correlations with interviews and grade point average provide evidence of construct validity. A time-limited essay with a clear scoring protocol results in adequate reliability and some validity.
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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 | 0.044 | 0.250 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".