Epistemic Stances: Local vs. Global, Reducible vs. Irreducible
Bibliographic record
Abstract
This paper addresses a gap in the scientonomic ontology by clarifying the notion of epistemic stance and articulating two orthogonal distinctions among epistemic stances: global vs. local, and reducible vs. irreducible. The paper first proposes cross-definitions of epistemic stance and epistemic element, completing the definitional loop among the basic scientonomic terms. It then introduces the distinction between global epistemic stances, understood as stances available to all epistemic agents transhistorically, and local epistemic stances, which are historically or agent specific. A second distinction is drawn between stances reducible to more fundamental stances (most notably theory acceptance) and those that are irreducible. These distinctions are illustrated through a classification of familiar scientonomic stances, such as theory acceptance, question acceptance, norm employment, and compatibility, as well as a discussion of such local stances as heresy, dogma, and scientificity. It then examines the conditions under which local epistemic stances become available to agents and deduces the local stance availability theorem, according to which the availability of a local stance depends on the derivability of permissibility or desirability norms from an agent’s mosaic. Finally, the dynamics of taking stances reducible to theory acceptance is explained by means of a theorem deduced from the law of theory acceptance. Several implications for future theoretical and observational scientonomic research are identified.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.035 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".