Bibliographic record
Abstract
The precise nature of the relationship between commerce and peace has long been a reliable source of contention between liberal and realist scholars. The commercial liberalism thesis, a subset of the broader liberal peace debate with roots running back to Kant, holds that trade promotes economic interdependence among states which in turn discourages war between them (Russett and Oneal 2001). While this basic argument continues to underpin the rosier scenarios concerning globalization, others—especially realists—remain skeptical, countering either that trade has little impact on the determinants of peace and conflict or that it exacerbates conflict as each partner seeks to gain at the expense of the other (Barbieri 2002). Despite the increasing methodological sophistication of this debate, which at its core revolves around the fundamental question of whether states care more about relative or absolute gains, it has remained both theoretically and empirically inconclusive. In The Political Economy of Transitions to Peace, Galia Press-Barnathan offers a new take on this old debate. Rather than focusing on the contribution of commerce to the prevention of conflict—what she terms the negative side of the liberal argument—her interest here is on whether economic ties linking former enemies can contribute positively to the building of peace between them. By focusing on peacebuilding between states, Press-Barnathan's book is a departure from much of the contemporary literature on post-conflict peacebuilding, which has been largely monopolized in recent years by a concern with intrastate, rather than inter-state, conflict. The author's underlying, if unstated, ambition is to contribute to a clearer understanding of whether and how economics can serve the cause of peace in troubled regions such as the Middle East.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".