Bibliographic record
Abstract
In the epistemology of disagreement literature an underdeveloped argument defending the claim that an agent need not conciliate when she becomes aware of epistemic peer disagreement is based on the idea that there are epistemic benefits to be gained from disagreement. Such benefits are unobtainable if an agent conciliates in the face of peer disagreement. I argue that there are good reasons to embrace this line of argument at least in inquiry-related contexts. In argumentation theory a deep disagreement occurs when there is a disagreement between fundamental frameworks. According to Robert J. Fogelin disagreements between fundamental frameworks are not susceptible to rational resolution. Instead of evaluating this claim I argue that deep disagreements can lead to epistemic benefits, at least when inquiry is in view. Whether rational resolution is possible in cases of deep disagreements, their existence turns out to be epistemically beneficial. I conclude by examining whether this line of argument can be taken beyond research-related contexts.Dans la littérature sur l'épistémologie du désaccord, un argument sous-développé pour une approche non conciliatoire se fonde sur l'idée qu'il y a des bénéfices épistémiques à tirer du désaccord. De tels bénéfices sont impossibles à obtenir si un agent se concilie face au désaccord avec ses pairs, du moins dans les contextes liés à la recherche. Dans la théorie de l'argumentation, un désaccord profond se produit lorsqu'il y a un désaccord entre des propositions cadres. Je soutiens que des désaccords profonds peuvent mener à des avantages épistémiques, du moins dans le contexte de la recherche. Que la résolution rationnelle soit ou non possible en cas de désaccord profond, leur existence s'avère être bénéfique sur le plan épistémologique.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".