The Influence of Messaging on Perceptions of Careers in Veterinary Medicine: Do Gender Stereotypes Matter?
Bibliographic record
Abstract
The veterinary medical workforce is increasingly female; occupational feminization often transfers stereotypes associated with the predominant gender onto the profession. It is unknown whether within veterinary medicine a feminized public image is a possible contributor to the reduction in male applicants to training programs. The influence of stereotypically gendered messaging on how male and female undergraduate students perceive veterinary medicine was investigated in 482 undergraduate students enrolled in five introductory or second-level biology courses. Two short videos introducing the field of veterinary medicine were developed with imagery and language selected to emphasize either stereotypic feminine ( communal) or masculine ( agentic) aspects of the field. Participant groups were randomly assigned one of the two videos (feminine/communal or masculine/agentic) or no video (no exposure). An outcome survey elicited impressions of the field of veterinary medicine and gathered demographic data. There was a significant linear trend of condition on perception of the profession as feminine or masculine and on perception of the activities of a veterinarian as feminine/communal or masculine/agentic. Female participants were significantly more likely to agree that someone of their gender would be valued in the profession. Male participants reported significantly higher self-efficacy scores for performing the tasks of a veterinarian when they viewed the feminine stereotype video. These results demonstrate that gendered perceptions of the field can be manipulated. Intentional gendered messaging should be further explored as one strategy to broaden the talent pool in the workforce by attracting men back to the field.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Experiment on gendered messaging and perceptions of veterinary careers; the object is a clinical profession's workforce, not the research workforce.
The study examines gendered perceptions of veterinary careers rather than the research workforce or research practice.
Gendered messaging and career perceptions in veterinary medicine concerns a clinical profession, not research careers or science practice.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".