Putting the ‘Classical’ in Neoclassical Realism: Neoclassical Realist Theories and US Expansion in the Post-Cold War
Bibliographic record
Abstract
This paper tests the explanatory power of the main strands of neoclassical realism in accounting for US foreign policy after the Cold War. According to the emphasis they place on the relevance of structural versus non-structural variables in foreign policy making, three schools can be identified. The first school restricts the role of non-structural factors to accounting for anomalous behavior; the second school argues that non-structural variables should also be included in order to understand the policy’s timing and style, and, in times of security plenty, its content; while the third school contends that it is international structural factors, i.e. a state’s strategic interactions with other polities, that shape most foreign policy. Following the test of their forecasts versus the historical record, the third school emerges as providing the most accurate account and as the most promising avenue of research for neoclassical realism.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".