Bibliographic record
Abstract
India’s year-long presidency of the G20 ended in late 2023. This had followed Indonesia’s presidency of the group in 2022, and Brazil assumed the presidency for 2024. While the rotational presidency being given to large emerging economies was seen as an essential and crucial step by many, the African Union’s (AU’s) elevation to a permanent seat in the organization was arguably even more important for amplifying the voice of the ‘global south.’ Given the transformation of the G20 with greater representation of the ‘global south,’ there is the question of how that voice is being used. For, as it was concluded by many that the G20 had not previously adequately represented emerging economies, then there is also the question of how the intended focus of the organization is being represented and adhered to. Of course, that does not imply that the organization was functioning purely for global benefit before, but it is valid to test how the transformation in G20 leadership and focus has translated to equitable action rather than simply working for ‘new’ vested interests. While a quantitative evaluation of India’s G20 presidency is not the focus here, it is worthwhile to make a broad overview of the outcomes. In that regard, we would assert that India’s presidency oversaw some important developments towards greater inclusivity in the consensus process of the organization. On the other hand, India ’s presidency brought with it the reality that leadership comes with some difficulties, and specifically, one cannot simply take the acclaim without criticisms and increased scrutiny. In terms of the inclusivity of the organization, the formal ascension of the AU to a permanent seat in the G20 during India’s presidency both broadened the participation of engagement to more emerging economies and was seen by many as a positive step towards the sustainability of the group. At the same time, though, the increased international scrutiny that India’s presidency theoretically exposed it to saw its strained relations with Canada highlighted more substantially than they otherwise may have been. In short, we would argue that India’s stewardship of the G20 for 2023 was significant, both symbolically and in terms of real outcomes. That stewardship, though, exposed India to more critical examination and provided a glimpse of the increased international scrutiny that India will be subject to as a rising power.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".