Publication Trajectories of Today's Canadian Academic Plastic Surgeons: A Bibliometric Analysis
Bibliographic record
Abstract
Introduction: The landscape of academic research has evolved notably in recent decades, shifting towards earlier career publications and more interdisciplinary collaborations. This study aims to identify research productivity trends among Canadian academic plastic surgeons. Methods: The Web of Science and MEDLINE databases were searched by plastic surgeon names and for each result, the author list position, year of publication, journal, and citation counts were collected. Surgeons’ demographics, including gender and medical school graduation year, were obtained from provincial college websites. Publication rates over a plastic surgeon's career trajectory were analyzed by surgeons’ current decade of practice. Results: There were 3661 included entries in our database, corresponding to 2831 unique publications by 245 surgeons (71%, 175/245 men). The median year of medical school graduation was 2002 (SD 12 years). Surgeons in more recent decades of practice (decade 1 or decade 2) published earlier and more frequently per career decade. A wide distribution of publication rates (range 0-66) was found for surgeons currently in their fourth decade of practice. From 2005 to 2020, the number of publications per year increased dramatically, from 36 publications in 2005 to 198 publications in 2020. Citations normalized by years from publication remained stable. The proportion of first authorship decreased from 0.63 and 0.42 in the pre-medicine and educational decades, to 0.09 and 0.08 by the third and fourth decades of practice (p < .001). Conclusion: An emerging trend of earlier and increased publications among newer generations of surgeons was seen. Incentives to participate and mentor in research for surgeons gaining seniority are suggested.
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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 | 0.002 | 0.613 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.131 | 0.182 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".