Using a Card Sort Technique to Determine the Perceptions of First-Year Veterinary Students on Veterinary Professionalism Attributes Important to Future Success in Clinical Practice
Bibliographic record
Abstract
First-year veterinary students' perceptions on the veterinary professionalism attributes important to future success in clinical practice were explored using a card sort technique. The key findings were that self-oriented attributes (overall mean: 3.20; 42% of responses rated essential) and people-oriented attributes (overall mean: 3.13; 39% essential) were rated more highly than task-oriented attributes (overall mean: 2.98; 31% essential) (1-4 scale: 1 = irrelevant, 4 = essential). Within these overall ratings, the establishment/maintenance of effective client relationships (people-oriented attribute; mean: 3.84) and the ability to be composed under pressure and recover quickly (self-oriented attribute; mean: 3.82) received the highest scores. The highest task-oriented score was the ability to work to a high standard and achieve results (mean: 3.57). There was no difference between ethnicities or between men and women, but respondents < 20 years of age gave higher scores to people-oriented attributes than did older respondents (≥ 20 years). The use of the card sort technique has not been widely reported in veterinary educational literature, and so this study represents a novel approach to garnering opinions from newly enrolled veterinary students-a group of stakeholders whose views on this subject are seldom sought. The results show that first-year veterinary students have well-developed opinions on the key attributes of veterinary professionalism and indicate that the early development of students' opinions needs to be taken into consideration in the design of professionalism curricula within veterinary programs.
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 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 | 0.010 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".