Bibliographic record
Abstract
The previous chapters have given plenty of good reasons to be suspicious about the use of persuasive definitions and emotive language in argumentation, and to often see them, especially when examining discourse from a logical point of view, as suspicious, or even as inherently illegitimate moves. But is it possible that rational persuasion can be shown to be a legitimate aim of argumentation by providing some kind of objective framework in which there are rules for proper persuasion? Is there a procedural setting in which a persuasion attempt could be an appropriate speech act properly employed so that, under the right conditions, it could be a legitimate move in rational argumentation? In this chapter we show how we need to study how definitions and arguments containing loaded terms are put forth as part of a sequence of argumentation in a dialogue exchange. The move made in a dialogue where a party puts forward an argument, or where a party puts forward a definition that she wants the other party to accept, needs to be seen as a kind of speech act that can only be properly understood in a rule-governed dialogue setting, we will argue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".