Bibliographic record
Abstract
Pourquoi les pays occidentaux versent-ils davantage d'aide au developpement aux autocraties qu'aux democraties ? Pourquoi le Danemark reussit-il a exercer une influence disproportionnee au sein de l'Union europeenne ? Pourquoi le Canada a-t-il fait du maintien de la paix la pierre angulaire de sa politique etrangere ? Ce manuel propose une introduction aux theories et aux methodes de l'analyse de la politique etrangere. Il passe en revue les principales approches, des classiques aux plus recentes. Plus qu'une simple synthese, il identifie les courants emergents, les lacunes qui doivent etre comblees, les donnees qui peuvent etre mobilisees, les pieges a eviter et les references bibliographiques a creuser. C'est le point d'entree incontournable pour tous les etudiants, les doctorants et les chercheurs qui entament un projet de recherche sur la politique etrangere. Jean-Frederic MORIN est professeur de relations internationales a l'Universite libre de Bruxelles, ou il enseigne notamment l'analyse de la politique etrangere.
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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.036 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".