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Record W2119566453 · doi:10.3138/jvme.28.3.122

Veterinary School Admission Interviews, Part 2: Survey of North American Schools

2001· article· en· W2119566453 on OpenAlexvenueaboutno aff
Grant H. Turnwald, Marlee M. Spafford, J D Bohr

Bibliographic record

VenueJournal of Veterinary Medical Education · 2001
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychologyVeterinary medicineMedical educationFamily medicine

Abstract

fetched live from OpenAlex

A study of veterinary school admission interview practices across the USA and Canada was conducted in 1999. All 31 schools responded. INTERVIEW USE: Eighty-four percent of the veterinary schools interview applicants. Veterinary schools are more likely to interview resident than non-resident applicants (62% interviewed >or=49% of their resident applicants, while 77% interviewed <or= 25% of their non-resident applicants).Seventy-two percent of the schools fix the interview weight in the selection process (mean weight is 28%). INTERVIEW PURPOSE AND CONTENT: The most common purposes for conducting a veterinary admission interview are to gather information, to measure non-cognitive/humanistic skills, and to clarify information on the written application (>or=77%). The five most common characteristics and skills the veterinary admission interview is intended to assess are communication skills, maturity, motivation for and interest in veterinary medicine, interpersonal skills, and knowledge of the veterinary profession (>or=92%). The least common characteristic or skill the veterinary admission interview is intended to assess is academic performance (23%). INTERVIEW FORMAT: Veterinary schools are most likely to offer one interview to a candidate (83%). A panel interview with between two and three interviewers is the predominant format employed (92%). The interview is of 20-45 minutes duration (88%), most commonly 30 minutes (50%). Interview questions most often address experiences in veterinary medicine, general background, and strengths and weaknesses (>or=85%). The level of interview structure is low to moderate (73%). The cold or blind interview (where interviewers are denied access to all or part of the written application) is employed by 50% of the interviewing veterinary schools. INTERVIEWERS: Interviewing veterinary schools assign interviewing to faculty veterinarians (100%). Some level of interviewer training is usually provided (87%); the most common mode of training is distribution of printed material (86%). SUMMARY AND RECOMMENDATIONS: The veterinary admissions interview is similar to that employed by schools of medicine, optometry, and dentistry, with the exception that veterinary schools are more likely to use panel interviews, to fix the interview weight in selection decisions, and to employ a cold or blind interview (these differences provide an opportunity to increase interview reliability and validity). Interview reliability and validity can be further improved by increasing interviewer training and interview structure, ensuring that the interview's format is consistent with its purpose, and identifying behavioral characteristics that are consistent with successful practice.

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)0.004
metaresearch head score (Gemma)0.011
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.460
GPT teacher head0.562
Teacher spread0.102 · 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 designObservational
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

Citations14
Published2001
Admission routes2
Has abstractyes

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