Роль бизнес-саммитов «Деловой двадцатки» во взаимодействии предпринимательского сообщества и власти на глобальном уровне
Bibliographic record
Abstract
The article investigates the summits of the «Group of Twenty» (G20) priority outreach-group – «Business Twenty» (B20), the activities of which are aimed at facilitating the development of sustainable economic growth which, in turn, would contribute to job creation as well as representation and protection of the interests of the national business communities in dialogue with the G20. The study of the «Business Twenty» models from the first summit in Toronto gives us the possibility to identify the main B20 meetings of broad participation within each chairmanship. The investigation suggests possible ways of classification and corresponding optimization of the B20 summits, mandatory meetings of the international business community, in accordance with three important criteria that exert a primary influence on the overall effectiveness and success of the outreach groupwork: they are mandatory character, publicity and the opportunity to meet the G20 leaders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.056 |
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; both teacher heads agree on what is shown here.
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".