Some Clarifications about the Argumentative Theory of Reasoning. A Reply to Santibáñez Yañez (2012).
Bibliographic record
Abstract
In “Mercier and Sperber’s Argumentative Theory of Reasoning: From Psychology of Reasoning to Argumentation Studies” (2012) Santibáñez Yañez offers constructive comments and criticisms of the argumentative theory of reasoning. The purpose of this reply is twofold. First, it seeks to clarify two points broached by Yanez: (1) the relation between reasoning (in this specific theory) and dual process accounts in general and (2) the benefits that can be derived from reasoning and argumentation (again, in this specific theory). Second, it suggests one domain—the categorization of arguments—in which argumentation studies and the argumentative theory of reasoning could usefully complement each other to yield a better understanding of the processes of argumentation.
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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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.008 | 0.018 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.029 | 0.033 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".