Bibliographic record
Abstract
This essay is part of a broader attempt to put some flesh on the bones of naturalistic jurisprudence. My general aim in this essay is to show that much contemporary jurisprudence takes a very narrow understanding of its subject matter, and gives priority, to the point of exclusivity, to one methodological approach – analytic philosophy – over all others. Unlike naturalistic analytic philosophy that welcomes ideas and data from other disciplines, the approach that dominates jurisprudence sees legal philosophy as concerned with certain questions that are uniquely philosophical and to which other disciplines have little to contribute. Some have challenged my past characterization of analytic jurisprudence as “isolationist.” My first aim in this essay is to show that this narrow approach is real. I begin by providing some empirical evidence on the narrowness of work in analytic jurisprudence (with special reference to work coming from Oxford). After showing that, I present some ways in which a naturalistic alternative would build on ideas or data coming from disciplines other than philosophy. In addition, I argue for two additional ways in which naturalistic jurisprudence differs from the current dominant approach. First, I suggest it should take the study of legal practice as central to its endeavor; and second, I suggest that legal philosophers themselves may be a relevant subject of study.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.012 |
| 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".