Rhetoric and ethic of dialog: Can conditions of performance serve as excluding criteria?
Bibliographic record
Abstract
First, we should recall that a rhetorical dimension is forcibly present in the performance of dialog, if we understand dialog both as an invitation and as a reciprocal openness for a constructive process; it can be demonstrated if we look at some proposals of dialog (Buber 1922, and more recently Isaacs 1999). Usually the refusal to consider that there is a rhetorical aspect aims to keep a specific communication process protected against undue manipulation or abuse; but a false assumption is then made. To guard us against such a slope, many authors have pleaded for a rhetorical ethic or an ethic of the rhetoric (Johannesen 19964). We should discuss whether some distinction should be made between valid and non valid forms of rhetoric, review the conditions of an ethical rhetoric, ask how and if they could be meaningfully used as criteria of exclusion (of the nonrhetorical as non-ethical and vice-versa).
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.048 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".