Bibliographic record
Abstract
Introduction In an agenda-setting essay first published in 2002, Lisa Martin and Beth Simmons argued that the study of international organizations (IOs) and institutions (IIs) had reached an important threshold, focusing less on why they exist and more on “whether and how they significantly impact governmental behavior and international outcomes” (Martin and Simmons 2002: 192). Put differently, the past decade has seen a sustained move by students of international institutions and organizations to viewing their subject matter as independent variables affecting state interests and policy. Conceptually, this has put a premium on identifying the mechanisms connecting institutions to states; methodologically, there has been a growing concern with measuring process. In this chapter, I assess several studies that make claims about international institutions influencing state-level action through various processes and mechanisms. The move to process and to the method of process tracing has been salutary, I argue, producing rich and analytically rigorous studies that demonstrate the multiple roles – good and bad – played by institutions in global politics.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.041 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| 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".