Bibliographic record
Abstract
The Group of Twenty (G20) was created first at the ministerial level and later upgraded to the summit level as a response to the global financial crises that first erupted from Asia in 1997, and then from the US in 2008 and Europe in 2010. These crises called into question the core principles and practices of the liberal order based on the economic, social and political openness that had been progressively internationally institutionalized since 1944. The G20 was designed with a dual distinctive foundational mission to promote financial stability and to make globalization work for all. It combined all established and emerging economies with high capability and connectivity, to operate as equals, to protect all within their borders and those beyond. It increasingly did so since its first summit in 2008. Its performance spiked at the summit in Hangzhou, China, on 3–4 September, 2016, and again at Hamburg, Germany, on 7–8 July, 2017. The latter coped with the new populist, protectionist US president and UK prime minister, whose countries had hosted the first three summits. G20-supported initiatives and agreements for full free trade have advanced since the first summit in 2008. No other center of global summit governance has emerged to guide an increasingly globalized world. The G20 has also steadily become an effective governor of global security. As the forces that propelled this rise will intensify, the Argentinian-hosted G20 summit on 30 November–1 December, 2018, promises to proceed along this path. It is guided by a country again afflicted by a financial crisis but now dedicated to following the core liberal order and making it work better for all. The real test will arrive in 2019, when Japan as host must co-operate with Korea and China, its neighbouring Asian powers and previous G20 hosts, to provide a new center of inclusive, progressive, liberal global governance that the world badly needs.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".