Conflict or Cooperation: A Survival Analysis of the Relationship between Regional Trade Agreements and Military Conflict
Bibliographic record
Abstract
Abstract This paper examines the timing behind the decision of countries to enter into regional trade agreements or interstate military conflicts, considering these two potential actions as substitute strategies. Using bilateral data from 1950 to 2014, I employ survival analysis to examine the factors that determine the likelihood of two countries entering into a regional trade agreement or a military conflict at any point in time. Historical or recent wars are posited to raise the gains from trade and therefore increase the likelihood that two countries choose to join the same trade agreement. On the other side, the existence of a strong trade relationship may raise the opportunity cost of entering into a conflict; bilateral trade flows and common membership in a regional trade agreement are posited to impact the likelihood of conflict. Other explanatory variables that affect the likelihood of either a common trade agreement or a military conflict include economic size, measured as the product of and the difference in the two countries’ GDPs; level of development, measured as the product of and the difference in the two countries’ per-capita GDPs; geography, measured by distance, contiguity, landlocked status, and island status; institutional linkages, represented by a common language, a colonial relationship, or a common legal origin; and political variables, including WTO membership, democracy, military alliances, and being a major oil producer. Results show that economic, geographic, institutional, and political variables all influence the probability that two countries enter into a conflict or join the same regional trade agreement.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".