Bibliographic record
Abstract
Abstract.The usual quantitative study of inter-state war and peace tallies observations on hundreds, sometimes thousands, of dyads or pairs of states. These observations miss elementary features of inter-state relations that should be examined when testing Realist explanations of war and peace. The way in which three prominent studies (Bremer, 1992; Bueno de Mesquita, 1981; 1985) chose to count the Seven Weeks War dramatically reveals the theoretical difficulties when tallying dyads. Re-analyses of these studies demonstrate the sensitivity of the results to particulars of 1866 Germany and, more importantly, illustrate the merits of analyzing the dispute rather than the state dyad or the state-dyad year. Résumé.L'étude quantitative des périodes de guerre et de paix entre États comptabilise des observations relatives à des centaines, parfois des milliers de dyades ou paires d'États. Ces observations ne prennent pas en compte certaines caractéristiques élémentaires des relations entre États qui devraient pourtant être examinées lorsque l'on teste les théories réalistes expliquant guerre et paix. La manière dont trois études reconnues (Bremer, 1992; Bueno de Mesquita, 1981; 1985) ont choisi de comptabiliser la guerre des Sept Semaines révèle de manière éclatante les difficultés théoriques dans la comptabilisation des dyades d'états. De nouvelles analyses de ces études ont démontré la sensibilité des résultats aux caractéristiques de l'Allemagne de 1866, mais soulignent surtout les mérites de l'analyse des disputes par rapport à l'analyse des dyades d'États ou des dyades d'États annuelles.
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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 | 0.012 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".