THE IMPACT OF CANADIAN-PRODUCED RESEARCH ON GLOBAL ORTHOPAEDIC LITERATURE: A BIBLIOMETRIC ANALYSIS
Bibliographic record
Abstract
Little is known about the quality and impact of Canadian-produced research relative to other developed nations. The purpose of this study was to determine 1) the global and national contribution of Canadian authors in the orthopedic literature, 2) the orthopedic productivity in Canada. We hypothesized that Canada ranks among the most impactful countries in terms of orthopedic research productivity. We performed a bibliometric analysis to identify articles published between 2001 and 2020 under the heading “orthopedics”. We identified: 1) Canada's global rank in terms of overall productivity, 2) individual Canadian authors' contribution, 3) quality of publications based on Category Normalized Citation Impact (CNCI) and publication in the top quartile of journals in terms of impact factor (%Q1), 4) percentage of Canadian publications attributable to orthopedics. We identified 10821 orthopedic publications from 2001 to 2020, of which Canada accounts for 7 th most globally. The annual productivity of Canadian orthopedic researchers had risen by a factor of 3.2. In terms of research quality, with a %Q1 of 36.5% and a CNCI of 1.22, Canada surpassed the USA, England, Germany, China, and Japan. Furthermore, orthopedic publications have accounted for 2.26% of overall Canadian scientific publications. The body of Canadian orthopedic literature has grown consistently over the past 20 years, and despite the overall leadership of the United States and other developed nations such as China and Japan, Canada ranks among the most influential countries in terms of quality and quantity of orthopedic research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.148 | 0.298 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".