Bibliographic record
Abstract
Metaethicists often specify non-naturalism in different ways: some take it to be about identity, while others take it to be about grounding. But few directly address the taxonomical question of what the best way to understand non-naturalism is. That’s the task of this paper. This isn’t a merely terminological question about how to use the term “non-naturalism”, but a substantive philosophical one about what metaphysical ideology we need to capture the pre-theoretical concerns of non-naturalists. I argue that, contrary to popular opinion, non-naturalism is best characterized not in terms of identity or grounding, but in terms of essence. First, I lay out some desiderata for a good characterization of non-naturalism: it should (i) speak to and elucidate the non-naturalist’s core pre-theoretical commitments, (ii) render non-naturalism a substantive, local claim about normativity, and (iii) provide the most general characterization of the view possible (iv) in a way that best fits the spirit of paradigm non-naturalist views. I then argue that identity characterizations fail to satisfy the former two desiderata, while grounding characterizations at best don’t satisfy the latter two. So, I propose a new essence characterization of non-naturalism and argue that it does a better job of satisfying all four desiderata. Moreover, I argue that this essence characterization has important implications for both metaethical and metaphysical theorizing.
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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.039 |
| Scholarly communication | 0.009 | 0.020 |
| Open science | 0.002 | 0.004 |
| 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".