Tracking Veterinary Students Who Aspire to Careers in Science
Bibliographic record
Abstract
The Cornell Leadership Program for Veterinary Students is an intensive 10-week learning experience intended to guide competitively selected scholars into careers in science and public health. It features independent research, vocational counseling, and student-directed learning modules. Program scholars are encouraged to objectively evaluate graduate training as preparation for careers promoted by the program. Prominence is given to experiential learning through research, participation in program enrichment modules, and inspirational experiences achieved through group meetings and individual interactions with established scientists. Program alumni are monitored to determine how the careers they pursue relate to their earlier-stated ambitions. In addition, subjective assessments are made of the quality of graduate training and its impact on alumni career paths. The influence of mentors, vocational counseling, and inspirational experiences on subsequent training is also subjectively assessed. Information is obtained from students' anonymous responses to questionnaires and recorded interviews. Program alumni are contacted annually to determine their current activities and career aspirations. The Leadership Program encourages program graduates to undertake careers in science and public health, yet an unanticipated number of alumni enter private veterinary practice. A factor relevant to that outcome is that many students destined for practice lack a definitive career plan. Persuading veterinary students to consider careers in research or public service is challenging but worth the effort. Critical to that connection is the need for veterinary students to objectively evaluate graduate training options because the vocations they follow appear to be strongly influenced by the experiences they choose.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".