Bibliographic record
Abstract
When it comes to the study of regional conflicts, realists as a group have been loath to put forward a clear and generalizable theory. This is not to say that realists have not offered insights into the probability of militarized conflict in particular regions. In the early 1990s, for example, John Mearsheimer and Aaron Friedberg offered well-known and controversial arguments for the likelihood of war in Europe and the Far East based largely on the insights of realist logic. Yet there are few realist scholars who have attempted to derive a theory of conflict that would predict the relative stability of different regions based on an understanding of the power dynamics within these regions, as opposed to simply examining how external great powers might exploit regional politics for their own purposes. This chapter will sketch the initial outlines of a realist theory that does seek to explain and predict the relative levels of stability across regions, both in historical terms and within the contemporary global system. Drawing on my previous work on major war between great powers, I will attempt to show that the logic of dynamic differentials theory (DDT), a structural realist theory designed to explain major wars at the level of the global great power system, can also be used effectively, with some qualifications, at the level of regional subsystems. Dynamic differentials theory argues that crises and wars are most likely when the most dominant military states in a system begin to anticipate steep and largely inevitable decline and thus start to fear the future intentions of rising actors. As I will discuss, whether these dominant states will initiate preventive attacks or destabilizing crises that might avert their decline will depend on a host of important structural variables, including the polarity of the system (in a regional subsystem, the number of important actors), the offense–defense balance, and the levels of relative economic and potential power. For now, it is important to grasp the essence of the approach: wars and militarized conflicts are driven by the dynamics of the power balance, and profound decline by the leading military state or its nearest rival can destabilize a system to the point of bilateral or subsystem-wide war.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".