L'affaire Nafissatou Diallo contre Dominique Strauss-Kahn: argumentation et émotios dans les journaux portugais et brésiliens
Bibliographic record
Abstract
[Extrait] Introduction Lors des deux dernières décennies, plusieurs réflexions théoriques ont ouvert une voie importante pour l'étude et la compréhension des rapports complexes qui unissent argumentation et émotion. Les travaux de Walton (1992, 2000), du côté anglophone, et ceux de Plantin (2011 b, 2012), de Micheli (2010, 2013), de Micheli, Hekmat et Rabatel (2013), du côté francophone, attestent de cet effort. Dans cette contribution, l'objectif est, d'une part, d'esquisser un éventail des stratégies multimodales (procédés linguistiques ou photos, parmi d'autres) utilisées dans les textes ou discours (plus ou moins émotionnés) sur l'affaire Nafissatou Diallo contre Dominique Strauss-Kahn — dorénavant ND vs DSK — dans des périodiques portugais et brésiliens ; d'autre part d'identifier les émotions sémiotisées 1 dans les textes à partir du choix de ces procédés. En adoptant le point de vue d'une analyse de(s) discours, on considère que l'étude de la construction des émotions doit être intégrée à l'étude de la dimension argumentative des genres de textes qui circulent dans des pratiques sociales. […]
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".