A argumentação no tribunal do júri: emoção e empatia do advogado de defesa em casos de homicídio
Bibliographic record
Abstract
Analisar a argumentação presente na sustentação oral de um advogado que defende um réu homicida e a sua relação com o convencimento dos jurados é o propósito deste trabalho. Dessa forma, fundamenta-se na nova retórica de Perelman e Olbrechts-Tyteca (1996); na sequência argumentativa de Adam (2011), em diálogo com as teorias de emoção, com Plantin (2011) e empatia com Rabatel (2013). Com a finalidade de padronizar a transcrição do corpus, ele foi passado para as normas do Projeto da Norma Urbana Oral Culta (NURC). A análise do dado aponta para os seguintes resultados: a sequência argumentativa seguiu o nível justificativo; sobre o argumento emocional, notamos que foi marcado por lexemas subjetivos; por fim, sobre o argumento empático, verificamos que os mais recorrentes foram a de que L1/E1 se colocar no lugar dos jurados, para evitar arrependimentos futuros, e, o do L1/E1 se colocar no lugar da mãe da vítima.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".