Bibliographic record
Abstract
Abstract: Two criticisms of the virtue-theoretic approach to argument appraisal are as follows. First, it is inadequate as argument cogency is conceptually independent of the characteristics of arguers (Bowell and Kingsbury 2013). Second, it is unmotivated since the viability of virtue argumentation theory (VAT) doesn’t require a virtue-theoretic approach to argument appraisal. This deflates the first criticism as an evaluation of VAT (Gascon 2016, Paglieri 2015). I consider each and explain why it is misguided highlighting the connection between the general concept of good argument and associated criteria of goodness, and the connection between good arguments and good arguing. Résumé: L’approche fondée sur la théorie de la vertu pour l’évaluation des arguments fait l’objet de deux critiques. Premièrement, elle est inadéquate, car la force de l’argument est conceptuellement indépendante des caractéristiques des argumentateurs (Bowell et Kingsbury 2013). Deuxièmement, elle est dénuée de motivation, car la viabilité de la théorie de l’argumentation fondée sur la vertu (AFV) ne nécessite pas une approche fondée sur la théorie de la vertu pour l’évaluation des arguments. Cela dévalorise la première critique en tant qu’évaluation de la AFV (Gascon 2016, Paglieri 2015). J’examine chacune de ces critiques et j’explique pourquoi elles sont erronées en soulignant le lien entre le concept général de bon argument et les critères de bonté qui lui sont associés, et le lien entre les bons arguments et la bonne argumentation.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".