Quelques perspectives de développement de l’étude empirique des conflits internationaux
Bibliographic record
Abstract
The empirical study of international conflicts has in the last two decades undergone a remarkable development. Careful examination of results so far obtained can however only produce feelings of dissatisfaction. The few correlations uncovered are usually so limited in scope that it is difficult to draw any conclusions whatsoever from them. This essay first of all suggests certain possible developments for empirical research, especially in areas which have been most neglected. The author goes on to show that the road on which such works are embarked, no matter how interesting, contains radical limits which can only invalidate the claims of practitioners of the empirical analysis of international conflicts to an elaboration of a truly explanatory theory. It will only be possible to discover explanatory elements if one undertakes a theoretical leap consisting in reorienting the study of international conflicts. The broad outlines of such a theoretical reorientation are described in the last part of the essay.
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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 | 0.028 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.005 | 0.040 |
| Scholarly communication | 0.019 | 0.023 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".