Les émotions présidentielles sous la Ve République : normes de sang-froid et régulation des émotions collectives
Bibliographic record
Abstract
Le président de la République doit-il montrer ses émotions ? Cet article vise à établir qu’une norme de sang-froid s’est construite au fil de l’histoire politique et s’est imposée sous la Ve République pour trois raisons : le sang-froid participe de la rationalisation du pouvoir d’État, il distingue ceux qui occupent des positions élevées, il procure une position de force dans les discussions. Néanmoins, s’il ne peut succomber aux émotions, le chef d’État ne doit pas pour autant ignorer celles-ci : il en orchestre la régulation, imposant par son discours des émotions collectives exemplaires, par exemple, à la suite d’attentats ou de décès de personnalités populaires. En comparant le rapport aux émotions du général de Gaulle à celui de ses derniers successeurs, en particulier Nicolas Sarkozy et Emmanuel Macron, on peut faire l’hypothèse d’un relâchement de la norme de sang-froid et d’une banalisation de l’expressivité des figures au sommet de l’État.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".