Veterinary School Admission Interviews, Part 2: Survey of North American Schools
Bibliographic record
Abstract
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.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".