Bibliographic record
Abstract
Epistemic stances play a foundational role in scientonomy’s explanatory framework, yet several of their currently accepted definitions fail to capture the concepts they are intended to explicate. This paper undertakes a systematic reassessment of epistemic stances, motivated by a series of conceptual ambiguities and inconsistencies that have emerged in recent theoretical and observational work. We begin by distinguishing epistemic stances understood as states from the transitions that initiate and terminate them, drawing on insights from formal ontology and related literatures. This distinction allows for a clearer formulation of scientonomic questions concerning the dynamics of scientific change. We then propose revised definitions of several core epistemic stances. In particular, we redefine theory acceptance in a way that permits suspension of judgment, multiple accepted answers, and theories answering multiple questions. We reconceptualize question acceptance as taking a question to be sound and introduce question answerability as a distinct epistemic stance. Norm employment is redefined as a dispositional state to act in accordance with a norm. Finally, we disambiguate norm rejection by differentiating transitions from norm acceptance to unacceptance and transitions from norm employment to unemployment; we suggest that the latter should be referred to as norm unemployment. We then outline corresponding revisions to scientonomic laws, theorems, and encyclopedia structure. Together, these revisions bring scientonomy’s explicit definitions of epistemic stances into closer alignment with our intuitive concepts and improve the coherence of our ontology.
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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.051 |
| Scholarly communication | 0.011 | 0.027 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".