Pre-matriculation Indicators of Academic Difficulty during Veterinary School
Bibliographic record
Abstract
The purpose of this study was to assess pre-matriculation academic and demographic data to identify risk factors for academic difficulty and failure to graduate among veterinary students. Admissions data were compiled for 1,098 students admitted to veterinary college between 1989 and 2000 inclusive. Students were classified by (a) academic success, consisting of students who completed veterinary school within four years in the top 90% of the class or (b) academic difficulty, including students dismissed for academic reasons, students who experienced academic delay, and students who graduated with a cumulative GPA in the 10th percentile of their class. Of 1,098 admitted students, 930 (84.7%) completed veterinary school within four years in the top 90% of their class. Among students with academic difficulty, 94 (8.6%) completed veterinary school in four years in the 10th percentile, 44 (4%) experienced academic delay, and 30 (2.7%) were dismissed. Academic difficulty was associated with a low prerequisite GPA, a low GRE score, poor undergraduate institutional selectivity, and older age (> or =35 years). Students who attended three-or-more undergraduate institutions or two-year colleges prior to attending a four year institution were 1.9 times more likely to experience academic difficulty and 3.87 times more likely to fail to graduate than students who attended a four-year institution (major or small) to complete their prerequisites. These study findings may assist with early identification of students at greater risk of experiencing academic difficulty and support the consideration of cognitive selection criteria (GRE and GPA) and undergraduate institutional experience during the admissions process.
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 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 | 0.001 | 0.009 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".