Patterns of International Collaboration for the UK and Leading Partners
Bibliographic record
Abstract
Patterns of international collaboration for the UK and leading partners are described by bibliometrical methods.The data analysed in this report are records of research publications,their authors' location and their subsequent citations by later publications.Data cover:nine countries - UK,USA,Canada,France,Germany,Japan,Australia,China and India;seven research fields-clinical sciences,health and related subjects,biological sciences,environmental sciences, mathematics,physical sciences,and engineering;two time periods - 1996-2000 and 2001-2005.Results show that the importance of international collaboration within countries' output has increased;for the UK the share of international collaboration has increased relative to domestic volume more rapidly than for other G7 economies;the UK retains a greater share of USA collaboration than any country except Germany;the average impact of internationally co-authored work is significantly higher than the overall average;the UK has more collaborative papers with China than any other EU partner.
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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 | 0.005 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.024 | 0.061 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".