Veterinary School Applicants: Financial Literacy and Behaviors
Bibliographic record
Abstract
Each year the Association of American Veterinary Medical Colleges (AAVMC) conducts a survey after the close of the Veterinary Medical College Application Service (VMCAS) application. The survey provides a glimpse into applicant behavior surrounding the veterinary school application process. Additional survey questions probe into applicant financial behaviors, use of financial products and services, and pet ownership. This article examines the 2013 survey data from applicants who successfully completed the application, with a focus on applicant financial literacy and behaviors. Data from the study revealed a disconnect between applicants' perception of their ability to deal with day-to-day finances and their actual financial behaviors, particularly for first-generation college student applicants and applicants who are racially/ethnically underrepresented in veterinary medicine (URVM). Many applicants were not able to accurately report the average veterinary school graduate's student debt level, which suggests the potential need for better education about the costs associated with attending veterinary school.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".