Bibliographic record
Abstract
Barry Carin- Senior Research Fellow at the Centre for International Governance Innovation, Waterloo, Ontario, Adjunct Professor at the University of Victoria, British Columbia, N2L 6C2, 57, Erb St. W., Waterloo, Ontario, Canada, E-mail: bcarin@cigionline.orgDavid Shorr- Program Officer at the Stanley Foundation, IA 52761, 209, Iowa Av., Muscatine, USA; E-mail: dshorr@stanleyfoundation.orgAbstractThe presented article analyses the G20 effectiveness. The authors discuss negative evaluations of this international multilateral institute and analyse the G20 agenda management to improve its effectiveness. The tools used by the G20 are also thoroughly explored. The authors argue that not only traditional methods (e.g. fulfillment of the commitments announced in summit communiques) should be used to assess the G20.The authors suggest recommendations on improving the G20 effectiveness. First of all, the G20 should focus on priority issues: food security, commodity-price volatility, challenges of energy and climate change. To keep the G20 from being overwhelmed by persistent agenda creep, it should devise ways to sunset its involvement with certain issues, perhaps by handing off efforts on an issue to other bodies or spinning them off into self-sustaining initiatives. Such filters as governance gap, global implications, need for high-level attention, complementarity, clarity, proportionate scale are recommended to develop the G20 agenda.In the authors’ view the real key to the G20 effectiveness is focusing all effort on the avenues that best rectify the given problem. The group can surely do better at contributing toward progress on the world’s urgent challenges, but the critique emphasizing distraction from its main business is neither a correct diagnosis nor a basis for constructive reform.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.080 | 0.024 |
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".