Vers une science de la politique internationale : Perspectives, promesses et résultats
Bibliographic record
Abstract
Concentrating on "the how of International Relations", this article deals in its first half with three major issues in scientific methodology : 1) importance of the scientific mode in acquiring and transmitting knowledge, and also rendering it more policy-relevant; 2) methods of forecasting international events and their evaluation; 3) different routes to theory-building : induction, deduction, analogy, gaming and computer simulation. The second half of the paper substantiates this methodological survey by presenting some findings from the Correlates of War Project that has been going on at the University of Michigan for two decades. The emphasis is on the rigorous identification of the phenomenon (War) and on the presentation of data on different factors at different levels of analysis correlated with its incidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.004 | 0.041 |
| Scholarly communication | 0.022 | 0.027 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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".