Bibliographic record
Abstract
Abstract: In this paper, we contend that there are two ways of arguing, namely sincere and insincere arguing. We draw such a distinction, based on the felicity conditions of the complex speech act of arguing as modelled in van Eemeren and Grootendorst’s pragma-dialectical approach. We introduce a conversa-tional setting, which contains a speech act of arguing that does not count as in-sincere arguing, while being a sui gene-ris form of sincere arguing. We desig-nate it as “cooperative inquiry”. Finally, we show that argument evaluation plays a key role in determining whether an in-stance of arguing counts as either argu-ing sincerely or insincerely. Résumé: Dans cet article, nous affir-mons qu’il existe deux manières d’argu-menter, à savoir l’argumentation sincère et l’argumentation non sincère. Nous établissons une telle distinction, basée sur les conditions de félicité de l’acte de parole complexe consistant à argu-menter, tel que modélisé dans l’ap-proche pragma-dialectique de van Eemeren et Grootendorst. Nous intro-duisons un cadre conversationnel, qui contient un acte de parole d'argumenta-tion qui n'est pas considéré comme une argumentation non sincère, tout en étant une forme sui generis d'argumentation sincère. Nous la désignons comme « enquête coopérative ». Enfin, nous montrons que l’évaluation des argu-ments joue un rôle clé pour déterminer si un cas d’argumentation compte comme une argumentation sincère ou non.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".