Oral maxillofacial surgery resident, faculty and practitioner role models and dental students' interest in oral maxillofacial surgery careers: Does gender matter?
Bibliographic record
Abstract
PURPOSE: Residency programs in oral maxillofacial surgery (OMS) have the lowest percentage (2020: 18.4%) of female graduates among all dental specialty programs. When considering this underrepresentation of female OMS residents, prior studies have not examined how OMS role models might shape dental students' interest in OMS careers. The objectives were to assess female versus male students' OMS-related career motivation, their experiences/attitudes toward three groups of OMS role models (i.e., OMS residents, faculty, and practitioners), and relationships between role model-related experiences/attitudes and career motivation. METHODS: 363 female and 335 male students from 14 United States and two Canadian dental schools participated in this cross-sectional study by responding to an online survey. RESULTS: 13.8% of female and 26% of male respondents (p < 0.001) were much/very much interested in OMS careers. More male than female students had shadowed an OMS in an office setting (43.4% vs. 35.1%; p < 0.05). The groups did not differ in their motivation to learn more and earlier about OMS nor in the quantity of OMS-related experiences prior to and during dental school. However, male students were more satisfied with the quality of these experiences (5-point scale with 5 = most positive: Means: 3.76 vs. 3.53; p < 0.05), were more comfortable approaching/working with OMS instructors (3.51 vs. 3.19; p < 0.01) and reported to have learned more from residents (3.52 vs. 3.31; p < 0.05) and faculty (3.75 vs. 3.45; p < 0.01) than female students. Female students agreed less that OMS residents, faculty, and practitioners encouraged students to pursue OMS (3.27 vs. 3.44; p < 0.01 / 3.46 vs. 3.63; p < 0.01 / 3.45 vs. 3.61; p < 0.01). Role model-related experiences and attitudes correlated with an interest in an OMS career. CONCLUSIONS: The two groups do not differ in the quantity of most OMS experiences before and during dental school and their motivation to learn more and earlier about OMS. However, female students' less positive OMS-related educational experiences and less positive attitudes toward role models correlate with a lower interest in OMS careers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".