Bibliographic record
Abstract
The rapid globalization of money, goods, services, taxation, knowledge, people, political ideas, digitalization, and especially pathogens and ecological pollutants has intensified, along with rising inequality, multipolarity, protectionism, isolationism and geopolitical tensions. Together these factors present new challenges to 21st century global governance led by the systemically significant states which make up the Group of Twenty (G20). G20 governance has expanded in response, but with more success on its old, incompletely globalized economic agenda than on its newer, more globalized digitalization, health pandemics and climate change agendas. The most recent G20 summit in Osaka, Japan on 28–29 June 2019 did make advances on tax and digitalization but not on the looming health risks and the existential threat of climate change. Preparations for the Saudi Arabian-hosted Riyadh summit, to be held on 21–22 November 2020, have made some progress on the latter amidst the unprecedented crisis posed by the COVID-19 pandemic. The crisis shows that the G20’s architecture needs to be further strengthened by institutionalizing G20 environment and health ministers’ meetings; inviting the executive heads of the United Nations (UN) bodies for climate change, biodiversity, the environment and health, as well as the leaders of key outside countries, to the summits; giving the UN and World Health Organization the same G20 status as the International Monetary Fund and World Bank; and holding a second annual summit at the UN each September focused on the sustainable development goals.
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 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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 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".