Ten. A State-Led Strategy of Decentralization: The BRICS Experience
Bibliographic record
Abstract
The BRICS ExperienceFrom vari ous theoretical and methodological perspectives, older and more recent studies on the production and circulation of academic knowledge describe hierarchies and inequalities on a global scale.Until rather recently, such studies largely converged on the idea that Western Europe and North Amer i ca were central in the academic worlds, and that what was perceived as their domination marginalized research in the Global South and in languages other than English. 1 However, the global academic landscape seems to be changing recently.Significant effort has been mobilized to create bridges between southern countries from the 1990s onward.While the fundamental prob lem of hierarchical and inequality structures persists, and the vari ous terminologies suggested to understand them remain relevant, we are currently observing a shift from North Atlantic centrism toward multipolarity. 2 Analysts have clearly observed the rise of Asian science, led by China (Kahn 2015, 106).China's gross expenditure on research and development (408.8 billion usd in 2015) was comparable to the total for the twentyeight EU countries (386.5 billion usd) and approaching that of the United States (502.9 billion usd).In 2015, China was the country with the largest absolute number of research staff (1.619 million full-time equivalents, compared with 1.380 million in the United States and 1.841 million in the EU; Shashnov and Kotsemir 2018, 1125).But not only China has moved to the forefront of such international comparisons.Before the formation of the brics alliance, during the 1990-2010 period, "the governments of the brics countries boosted their investments in research and development ten / wiebke keim and ari sitas
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 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".