Agreeing to Differ: Modelling Persuasive Dialogue Between Parties With Different Values
Why this work is in the frame
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Bibliographic record
Abstract
In some cases of disagreement, particularly in ethics and law, it is impossible to provide any conclusive demonstration. The role of argument in such cases is to persuade rather than to prove. Drawing on ideas ofPerelrnan, we argue that persuasion
 in such cases relies on a recognition that the strength of such arguments will vary according to their audience, and depends on the comparative weight that the audiences gives to the social values that it advances. To model this, we introduce the notion of Value-based Argumentation Frameworks (VAFs),
 an extension of Argumentation Frameworks as originally introduced by Dung. We then describe a dialogue game based on VAFs, designed to model persuasive argumentation, which we illustrate with a widely discussed ethical problem.
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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 it