RATES OF BURNOUT IN FEMALE ORTHOPAEDIC SURGEONS CORRELATE WITH BARRIERS TO GENDER EQUITY
Bibliographic record
Abstract
The purpose of this study was to investigate the relationships between career burnout and the barriers to gender equity identified by Canadian female orthopaedic surgeons. A secondary purpose was to assess relationships between the female surgeons' demographic characteristics and career burnout and job satisfaction. An electronic survey was distributed to 330 Canadian female orthopaedic surgeons. Demographic variables including age, stage and years of practice, practice setting, and marital status were collated. The survey included the Gender Bias Scale (GBS) questionnaire and two questions each about career burnout and job satisfaction. Pearson r correlation coefficient evaluated the relationships between the higher- and lower-order factors of the GBS, burnout, and job satisfaction. Spearman rank correlation coefficient assessed relationships between burnout, job satisfaction, and demographic variables. Survey responses were received from 218/330 (66.1%). Agreement or strong agreement for career burnout was reported by 110/218 (50.5%) of the surgeons (median=4). Burnout was positively correlated with the GBS higher-order factors of Male Privilege (r=0.215, p<.01), Devaluation (r=0.166, p<.05), and Disproportionate Constraints (r=0.152, p<.05). Job satisfaction was reported by 168/220 (77%) of the surgeons (median 4), and 66% were also satisfied or very satisfied with their role in the workplace (median 4). Burnout was significantly negatively correlated to surgeon age and job satisfaction. Over 50% of female orthopaedic surgeons reported symptoms of career burnout. Statistically significant relationships were evident between burnout and barriers to gender equity. Identification of the relationships between gender-equity barriers and burnout presents an opportunity to modify organizational systems to dismantle barriers and reduce this occupational syndrome.
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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 | 0.003 | 0.001 |
| 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) | 0.000 | 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".