Neoclassical Realism as a Theory for Correcting Mistakes: What State X Should Do Next Tuesday
Bibliographic record
Abstract
Abstract Neoclassical realism has carved a unique niche by offering a theoretically derived and empirically rich foreign policy analysis framework. Over the years, it has branched out as a theory of mistakes (Type I), a theory of foreign policy (Type II), and a theory of international politics (Type III). This article proposes another challenge to consolidate its offer of a progressive research agenda to position it as a theory for correcting mistakes. The theory of mistakes version differentiates ideal from actual foreign policy. The ideal corresponds to foreign policy that follows the pressures and incentives of the international system; structural realism, the basis for this optimal baseline, is here viewed as a normative theory. If there is a gap between the ideal baseline and the actual outcome, then foreign policy is sub-optimal and therefore costly. According to neoclassical realists, this is the result of the intervention of domestic political processes hijacking foreign policy. It follows that pointing out how to reduce the distorting impact of these domestic variables should help steer foreign policy toward optimality. By identifying the negative consequences that follow from a sub-optimal foreign policy, a theory for correcting mistakes also opens the door to developing prescriptions to manage the inevitable fallout.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".