Reclaiming what is ours: Elite continuity and revanchism
Bibliographic record
Abstract
Abstract What explains the revanchism of (post-)imperial states? This question has renewed salience amid Russia’s expanded war against Ukraine in 2022. In this article, we conceptualise revanchism as a foreign policy preference that involves reclaiming territory once controlled. We also advance a new explanation for revanchism that emphasises elite continuity in those states that experience territorial loss. Elite continuity matters because the ruling political class in (post-)imperial states, which was socialised under the old regime, preserves certain beliefs about world politics and the perceived legitimacy of their territorial claims. We show that elite continuity between the Soviet and post-Soviet political leadership in Moscow helps explain Russia’s revanchism better than those alternative explanations that we derive from the International Relations literature. To substantiate our argument, we compile a novel dataset to operationalise elite continuity across regimes and use discursive evidence and other indicators of elite attitudes towards the desirability of reclaiming lost territory. We also discuss the applicability of our theory to other cases.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".