Разделение труда - разделение ответственности?
Bibliographic record
Abstract
Marina Larionova, Dr of Political Science, Head of International Organisations Research Institute (IORI) of the State University - Higher School of Economics, Head of International Programmes at the National Training Foundation; E-mail: mlarionova@hse.ruMark Rakhmangulov, Deputy Director of the Informational-Analytical G8 Research Centre of the International Organisations Research Institute (IORI) of the State University - Higher School of Economics; E-mail: MRakhmangulov@hse.ru The paper presents analysis of the G8 Muskoka and G20 Toronto summits. It looks into the main documents agreed and decisions made by the leaders. The authors consider the trend for division of labor on priorities and global governance functions between the two institutions, and the risks it contains. The analysis highlights that the G8 members so far bear the dual responsibility for commitments made in both the G8 and G20 summits. The G8 members have also delegated significant volume of the direction setting and decision making functions to the G20. It can be assumed that the Seoul summit will change the trend. However the paper concludes that if the Muskoka-Toronto summitry distribution of functions is maintained and consolidated, and the G20 compliance record remains low, the G8-G20 partnership for global governance will be neither sustainable nor effective.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".