Investigating Gender Differences in Canadian Plastic Surgery Online Patient Education
Bibliographic record
Abstract
BACKGROUND: The public interest and demand for cosmetic surgery is growing in North America. As practices continue to advertise cosmetic procedures, male consumers must also be given fair consideration in a market targeted mostly towards women. OBJECTIVES: This study investigated the advertising trends of plastic surgery clinics to assess for prevailing gender differences among online Canadian plastic surgery practice advertising. METHODS: The 2021 College of Physicians and Surgeons directory for each province and territory was utilized to identify all practicing plastic surgeons. A systematic search with Google (Mountain View, CA) was conducted to analyze the websites of Canadian plastic surgery centers in the following manner: "[physician name] [province of practice]." RESULTS: A total of 209 websites and 13,838 images were identified and analyzed. Of these images, 12,386 (90%) were female and 1452 (10%) were male patients or models. Although only 20% had a male services page, 62% of all centers offered gynecomastia procedures. The most common procedures targeting men were blepharoplasty (95%), liposuction (93%), and abdominoplasty (93%). The Prairies region had significantly fewer websites with male-only pages compared with all other Canadian regions. CONCLUSIONS: Despite the increase in cosmetic surgery procedures for males, the market for cosmetic surgery procedures targeted towards males remains insignificant. An increase in the advertising of in-demand male cosmetic procedures can allow for a broader consumer market and a subsequent increase in benefits for plastic surgeons.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".