MétaCan
Menu
Back to cohort
Record W2056197273 · doi:10.3138/jvme.37.3.254

Using Standardized Essays in the Veterinary Medicine Admissions Process: Are the Ratings Reliable and Valid?

2010· article· en· W2056197273 on OpenAlexaffvenueabout
Kent G. Hecker, Claudio Violato

Bibliographic record

VenueJournal of Veterinary Medical Education · 2010
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsHealth Sciences CentreUniversity of Calgary
Fundersnot available
KeywordsGeneralizability theoryReliability (semiconductor)Construct validityPsychologyScale (ratio)ValidityMedicineClinical psychologyPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.129
GPT teacher head0.469
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2010
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical EducationSame topicMedical Education and AdmissionsFrench-language works237,207