Towards a richer model of deliberation dialogue: Closure problem and change of circumstances
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Models of deliberative dialogue are fundamental for developing autonomous systems that support human practical reasoning. The question discussed in this paper is whether existing models are able to capture the complexity and richness of natural deliberation. In real-world contexts, circumstances relevant to the decision can change rapidly. We reflect on today’s leading model of deliberation dialogue and we propose an extension to capture how newly exchanged information about changing circumstances may shape the dialogue. Moreover, in natural deliberation, a dialogue may be successful even if a decision on what to do has not been made. A set of criteria is proposed to address the problem of when to close off the practical reasoning phase of dialogue. We discuss some measures for evaluating the success of a dialogue after closure and we present some initial efforts to introduce the new deliberation features within an existing model of agent dialogue. We believe that our extended model of dialogue may contribute to representing that richness of natural deliberative dialogue that is yet to be addressed in existing models of agent deliberation.
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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