An Exploration of the Career Motivations Stated by Early-Career Veterinarians in Australia
Bibliographic record
Abstract
Despite the critical influence of motivation on education and work outcomes, little is known about the motivations driving people to become and remain veterinarians. This qualitative study explored the career motivations stated by Australian veterinary graduates ( n = 43) using a free-response Ten Statements Test (TST) at graduation, with follow-up interviews 6–8 months later ( n = 10). TST responses were coded using an alternate inductive-deductive approach that tested their fit against existing theories of motivation. Results showed that the stated motivations were predominantly oriented to perceived value, rather than self-beliefs such as expectancy of success. About a quarter of the statements were animal-related, principally themed around intrinsic animal orientation (e.g., I like animals) or extrinsic animal-related purpose (e.g., I want to help animals). However, many non-animal themes also emerged, including both intrinsic (e.g., love of learning, challenge/problem solving, variety, social relatedness) and extrinsic (e.g., helping people, social contribution, career opportunity) motivations. Interview data revealed a motivational narrative of early formative influences, with some interviewees describing a later transition toward more people- or goal-oriented motivations. This exploratory study, outlining a broad taxonomy of veterinary career motivations and their alignment to self-determination theory in particular, may provide a useful framework for exploring career motivations in veterinary education.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".