Bibliographic record
Abstract
Source importante de conflit en politique internationale, l’honneur pousse certains dirigeants à prendre de grands risques pour venger des humiliations subies ou perçues. Les préoccupations d’honneur ont joué un rôle primordial dans la politique étrangère revancharde et révisionniste de Donald Trump. Soucieux de l’image internationale des États-Unis, Trump a assumé le rôle de redresseur de torts en chef : il a exigé réparation autant aux alliés et partenaires qui profitaient des États-Unis qu’aux rivaux et ennemis qui ne respectaient plus la puissance américaine. Réimposer le respect et venger les humiliations ont été, depuis 2017, des objectifs prioritaires de sa « politique étrangère des griefs ». C’est en particulier en 2020, année électorale, qu’on a pris la pleine mesure de l’importance des préoccupations d’honneur dans son approche singulière, comme l’a illustré sa gestion des relations avec l’Iran et la Chine.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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; both teacher heads agree on what is shown here.
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".