The Institutional “Hinge”: How the End of the Cold War Conditioned Canadian, Russian, and Swiss IR Scholarship
Bibliographic record
Abstract
Abstract Major international events contribute to guiding IR scholarship's interests, yet it remains surprisingly unexplored how transformative political events affect international relations as an academic field. This article focuses on the linkage between key global moments and the institutional factors that condition IR scholarship, focusing on the important yet under-explored intervening elements in the interrelation between political events and academic practice. The article defines the utility of such focus and illustrates it with case studies of three central parties to the Cold War conflict: Russia as representative of the Eastern bloc, Canada of the Western alliance, and Switzerland as a neutral polity. This article shows how institutional factors such as funding schemes, the marketization of education, and the creation of new IR departments operate as effective “hinges” exerting significant influence over the ways scholars develop ideas about international relations.
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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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.038 | 0.057 |
| Scholarly communication | 0.034 | 0.005 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".