Bibliographic record
Abstract
The international political economy of oil has multiple, important influences on peace and security. Oil-exporting states, or petrostates, engage in militarized interstate disputes (MIDS) at a much higher rate than non-petrostates. Why are some but not all petrostates inclined to adopt dissatisfied, aggressive foreign policies and to engage in MIDS on that basis? This paper investigates this question by testing a theory that proposes that when revolutionary regimes come to power in petrostates, they have a dramatically higher propensity to engage in MIDS than comparable non-petrostates. This theory is tested with statistical regression analysis using a new quantitative dataset that identifies revolutionary regimes in the period 1945-2001. The results show that petro-revolutionary regimes constitute a special threat to international peace and security. This evidence implies that one of the standard explanations of the relationship between revolution and war, based on a theory of balance of threat, is not fully satisfactory. Moreover, the findings challenge the conventional understanding of the link between oil and war. Readers Note: This paper is a modified draft version of the quantitative empirical chapter of my dissertation on International Security and Oil-Exporting States. As such, it is meant to be read in connection within a larger whole, but where possible I have tried to give context from the rest of the dissertation in this paper. Thanks are owed to my dissertation committee Robert Keohane, Christina Davis, and Jennifer Widner, as well as to Sarah Bush, Jessica Green, Mark Melamed, and Jordan Tama for comments on earlier drafts of this paper. Financial support from the Bradley Foundation, the Woodrow Wilson School, and the Social Sciences and Humanities Research Council of Canada is gratefully acknowledged. Oil and Revolutionary Regimes: A Toxic Mix Jeff Colgan, 2008
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.028 | 0.003 |
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".