Bibliographic record
Abstract
This chapter offers further qualitative evidence on the link between new democracies and IO formation and demonstrates the broader applicability of our theory. The chapter begins by describing the experiences of the Caribbean states, primarily Barbados, in forming CARIFTA and of the Southern Cone states, primarily Uruguay, in forming Mercosur. Both cases are clear examples of the mechanism highlighted throughout the book: democratizing states creating brand-new IOs. Moreover, both cases continue to illustrate how this process is assisted by established democracies. Canada, the United States, and Britain assisted CARIFTA, while the established democracies of the EU supported Mercosur. Next, the chapter moves to a case of remodeling and a case of reforming. Remodeling will be illustrated by the South African Development Community, while reforming will be illustrated by the OAS and its Unit for Democracy Promotion. Overall, these cases show how the IOs offered technical and material assistance in the provision of public goods. IO membership is not a panacea, but IOs do increase the odds of democratic consolidation.
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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 | 0.001 |
| 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 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".