Orthopaedic Travelling Fellowship Programs: A Survey of Canadian Applicants and Participants
Bibliographic record
Abstract
Background: Despite the well-documented benefits of travelling fellowships, there is a lack of female applicants to travelling fellowship programs. There is also a limited amount of research that has been conducted regarding travelling fellowships. Therefore, the aims of this study were fourfold: (1) to determine the number and gender of successful applicants for fellowship programs, (2) to determine any perceived barriers for both men and women to participating in travelling fellowship programs, (3) to explore possible support systems to address these barriers, and (4) to explore any differences among genders regarding perceived barriers to participating in travelling fellowship programs. Methods: A 41-item cross-sectional survey was distributed to all Canadian Orthopaedic Association (COA) members who applied for a COA travelling fellowship program between 2004 and 2019. There were 78 applicants of which 26 were women (33%). Up to 3 reminder emails were sent every two weeks after the initial invitations to encourage participation. Descriptive statistics were performed. Results: A total of 103 fellowship applications were submitted, 26% from female applicants. Thirty-one (39%) of the applications submitted by men were successful and 10 (33%) of the applications submitted by women were successful. Nineteen individuals completed the survey with a gender distribution equal to the non-responders. The most common perceived barriers were time constraints (65%) and family obligations (47%), with 24% of respondents identifying no perceived barriers at all. No respondent identified concerns for sexual or gender-based harassment. Eightyfive percent of individuals responded that the perceived barriers were not related to their gender. Most respondents (87%) suggested a mentorship program to increase the number of female applicants to COA travelling fellowship programs. Conclusions: Women are less likely to apply for orthopaedic travelling fellowships in Canada; however, the success rate of applications submitted by women is similar to that of applications submitted by men. When applying to COA travelling fellowship programs, the majority of applicants identified barriers including time constraints and family obligations. In general, these barriers were not perceived to be related to their gender. The findings of this study may encourage more women to apply to COA travelling fellowship programs.
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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 | 0.018 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.036 | 0.088 |
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; both teacher heads agree on what is shown here.
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".