Trends in American and Canadian Contribution to the Otolaryngology Literature
Bibliographic record
Abstract
Objectives: Assess the 2008‐2012 American and Canadian contribution to the world otolaryngology literature. Methods: All articles published from January 2008 to December 2012 in 8 otolaryngology journals were reviewed. Book reviews, letters, correspondence, and meeting abstracts were excluded. Nationality, author numbers, and study types were extracted. Nationality of the article was defined by the publishing department's country of origin. Articles were categorized into primary clinical research, primary basic science research, secondary research such as systematic reviews and meta‐analyses, and other articles that did not fit the aforementioned classifications. Articles originating from the United States, Canada, and the rest of the world were statistically compared using Mantel‐Haenszel Common Odds Ratio Estimate, Pearsons chi‐squared, and Fisher exact tests. Results: A total of 3635 articles published in the journals surveyed were analyzed. Canadian‐authored papers decreased from 12.8% in 2008‐2009 to 10.2% in 2011‐2012, whereas American‐authored papers increased from 27.9% in 2008‐2009 to 30.1% in 2011‐2012. These changes were statistically significant (P =. 031). Multiauthorship (≥5 authors) increased in Canadian papers (P =. 015), whereas this trend had not been observed in American papers (P =. 566). Study types from the United States and Canada had not significantly changed from 2008‐2009 to 2011‐2012 (P =. 137). Conclusions: There were significant changes in otolaryngology publishing trends in the United States and Canada. Increase in multiauthorship in Canadian‐authored papers possibly suggests increased collaboration with multi‐disciplines and decreased investigator productivity.
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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 | 0.016 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.055 | 0.067 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".