Bibliographic record
Abstract
De part et d’autre de l’Atlantique, les acteurs politiques et militaires semblent de moins en moins d’accord sur l’opportunité d’intervenir militairement sur les lieux d’intervention et sur les modalités des emplois de la force armée. Pourquoi ? L’objectif de l’article est d’explorer les sources des divergences transatlantiques relatives à la force armée en analysant comment les dirigeants politiques et militaires en Europe et aux États-Unis perçoivent les problèmes que soulèvent la puissance militaire et ses usages. Nous examinons, tout d’abord, les problématiques disponibles pour rendre compte des divergences transatlantiques avant d’indiquer l’approche que nous retiendrons qui met l’accent sur les perceptions et le rôle des institutions militaires. Ensuite, nous présentons les différences des perceptions de la puissance militaire de certains acteurs politiques aux États-Unis et en Europe. Enfin, nous identifions les principales caractéristiques des conceptions de l’emploi de la force armée aux États-Unis et en Europe.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".