Bibliographic record
Abstract
The main rationale for adopting the epistemological approach to argumentation seems to take the form of a criticism of the consensus theory. This criticism says that some instances of clearly bad argumentation count as acceptable instances of argumentation on the consensus theory. Supposedly, the epistemological approach does not have this problem. I suggest that the kind of normativity argumentation theorists should be concerned with is the normativity associated with giving real-world advice on how to partake in a critical discussion. I try to show that when we understand the normativity of argumentative standards in this way, the main criticism of the consensus theory falls short, and the epistemological approach does not really have the advantages over the consensus theory that it is purported to have. If I am right, then the main reason offered for adopting the epistemological approach fails, and we should stick with the consensus theory.
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 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 | 0.107 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.014 | 0.112 |
| Scholarly communication | 0.023 | 0.034 |
| Open science | 0.009 | 0.013 |
| Research integrity | 0.024 | 0.029 |
| Insufficient payload (model declined to judge) | 0.005 | 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".