Mapping the epistemic arguments for religious toleration
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
Abstract In the literature on toleration, epistemic arguments are commonly equated with John Stuart Mill's fallibilism according to which toleration of opinions is a necessary means to the attainment of truth. This conflation does not capture the variety of those arguments and it results from the fact that a proper analysis of epistemic arguments for religious toleration and a systematic account of their different types are still lacking. The purpose of this article is to provide such an analysis and to argue that those arguments come in four different types, which I name fallibilism, religious belief-forming process, epistemic parity, and differentiated access to religious truth or divine message. I also offer a mapping of those different types of arguments using the standard epistemic notions of justification, truth, and belief coupled with a distinction of focus in the epistemological approach – whether individually or socially focused.
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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 | 0.001 | 0.000 |
| 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 it