Key Trends in the Making of Global Policies
Bibliographic record
Abstract
Building on comparative analysis, this chapter identifies ten trends that we feel capture key dynamics of global policymaking in the early twenty-first century: the clash of sovereignties, the growing focus on individuals, the universalization of aspirations, the promotion of a holistic narrative, the orchestrating role of international organizations, the pursuit of inclusion, increasing codification, the emphasis on expertise, the resilience of the North–South divide, and Western hegemony. The arrangement of these dynamics, which embody a combination of practices and values, obviously differs across issue areas. Nonetheless, most of these ten trends are observable in pretty much any instance of global policymaking today. The ultimate goal of this comparative exercise is to determine whether there are (1) practices that recur more often than others and (2) worldviews that seem to regularly triumph over others. Among others, we observe that sovereignty remains central to global governance but sometimes in heterodox ways; codification is a much more diverse process than legalization; orchestration is as much about cooperation as it is about competition and collusion; and North–South politics can give way to unexpected alignments.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".