Les stratégies de politesse en situation de « double contrainte » dans le débat télévisé des chefs de 2008 au Canada
Bibliographic record
Abstract
A l’aide des theories sur le systeme de la politesse, cette recherche a pour but de decrire les strategies verbales utilisees par les cinq participants lors du debat politique national televise des chefs de 2008 au Canada, alors qu’ils devaient suivre la consigne particuliere de flatter l’un de leurs adversaires. L’analyse demontre l’utilisation de mecanismes communs et divergents entre eux, au niveau des actes langagiers flatteurs et des actes langagiers menacants. Cette contribution originale nous eclaire davantage sur les strategies de politesse dans les debats politiques, plus notamment lors d’une situation de « double contrainte » tres prononcee. Using theories about politeness, this paper aims to describe the verbal strategies used by five political leaders during the national leaders’ debate televised in Canada in 2008. The leaders were asked to make positive comments about one of their opponents. The analysis shows shared and divergent mechanisms, including both Face Flattering Acts and Face Threatening Acts. This original contribution provides a better understanding of politeness strategies in political debates and, in particular, in the very explicit situation of “double bind.”
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".