Right out of the box: how to situate metaphysics of science in relation to other metaphysical approaches
Bibliographic record
Abstract
Several advocates of the lively field of “metaphysics of science” have recently argued that a naturalistic metaphysics should be based solely on current science, and that it should replace more traditional, intuition-based, forms of metaphysics. The aim of the present paper is to assess that claim by examining the relations between metaphysics of science and general metaphysics. We show that the current metaphysical battlefield is richer and more complex than a simple dichotomy between “metaphysics of science” and “traditional metaphysics”, and that it should instead be understood as a three dimensional “box”, with one axis distinguishing “descriptive metaphysics” from “revisionary metaphysics”, a second axis distinguishing a priori from a posteriori metaphysics, and a third axis distinguishing “commonsense metaphysics”, “traditional metaphysics” and “metaphysics of science”. We use this three-dimensional figure to shed light on the project of current metaphysics of science, and to demonstrate that, in many instances, the target of that project is not defined with enough precision and clarity.
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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 | 0.033 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.008 | 0.102 |
| Scholarly communication | 0.019 | 0.047 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 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".