Veterinary Students and Their Reported Academic and Personal Experiences During the First Year of Veterinary School
Bibliographic record
Abstract
Veterinary students completed an online survey regarding personal and academic concerns they experienced during their first year of veterinary school. Quantitative results showed a high degree of stress and anxiety among the study participants as well as concerns about time management and study skills. Quantitative analysis using chi-square tests revealed significant associations between concerns about study skills and the independent variables of relationship status and time since obtaining an undergraduate degree. Results of a thematic analysis undertaken with the qualitative data provide further insight into first-year experiences, indicating concerns about the intensity of the program and especially about time commitment, the amount of information students were expected to learn, and the amount of material they were expected to memorize. Another theme revealed that students did not feel academically prepared for some of their first-year courses, which led to their not liking those courses for which they lacked appropriate groundwork. Other themes highlighted the students' desire for more clinically relevant experiences during their first year as well as surprises regarding the maturity level of classmates and the level of support offered by professors. Given the results of this study, suggestions for counselors and others who work with veterinary students are provided.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".