Bibliographic record
Abstract
Abstract: This paper critically examines the ongoing debate over the legitimacy of visual arguments and proposes a resolution to this issue. Using a type-theory framework, the legitimacy of visual arguments is addressed through two key sub-problems. First, the paper argues that visual arguments exist, with their existence grounded in dynamic existentialism. Second, it contends that visual argumentation theory can expand argumentation theory in both descriptive and normative aspects. The paper advocates for a moderate defense of visual arguments, offering a stronger foundation for future research in the field. Résumé: Cet article examine de manière critique le débat actuel sur la légitimité des arguments visuels et propose une solution à ce problème. En s'appuyant sur la théorie des types, la légitimité des arguments visuels est abordée à travers deux sous-problèmes clés. Premièrement, l'article soutient l'existence des arguments visuels, fondée sur l'existentialisme dynamique. Deuxièmement, il soutient que la théorie de l'argumentation visuelle peut élargir la théorie de l'argumentation, tant sur le plan descriptif que normatif. L'article prône une défense modérée des arguments visuels, offrant ainsi une base plus solide aux recherches futures dans ce domaine.
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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 | 0.027 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 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".