Working Together for G8-G20 Partnership: The Muskoka-Toronto Twin Summits, June 2010
Bibliographic record
Abstract
John J. Kirton, Dr. of International Relations, Director of the G8 Research Group, Associate Professor of Political Science, Research Associate of the Centre for International Studies and Fellow of Trinity College at the University of Toronto, Canada; E-mail: john.kirton@utoronto.caThe article examines how and why Canada’s twin 2010 summits worked well separately and together, and how the future G8-G20 partnership can be improved to the benefit of both in the years ahead. The author makes the comparative analysis of the performance of Muskoka G8 and Toronto G20 summits, identifying the synergistic convergence, and explores the causes of the successes and shortcomings of each alone and both together applying the closely related but distant concert equality model of G8 governance and the systemic club model of G20 governance as analytical guides. On the basis of this analysis, the author suggests the ways for strengthening G8-G20 partnership.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".