Bibliographic record
Abstract
Most people think of law as an instrument that can help us achieve human purposes that can themselves be adequately specified without reference to law or legal ideas. But a number of scholars, associated in various ways with the natural law tradition in jurisprudence, have argued that we should understand law non-instrumentally, in the sense that its role is to constitute rightful relations between people, where the rightfulness of these relations cannot be specified apart from the legal ideas, institutions, principles, and rules that constitute them. On this view, the law cannot be instrumental because its purpose cannot be understood independently of the way it achieves that purpose. In this paper, I argue that these two views are compatible to the following extent. Even if the point of the legal order as a whole is to constitute a state of affairs that is rightful in a sense that cannot be characterised apart from legal ideas, instrumental reasoning about the causal effectiveness of particular laws in achieving particular purposes is not precluded, indeed is essential, provided those purposes are themselves understood as contributions to the constitution of just relations between people rather than as contributions to the achievement of some independently defined good.
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 | 0.028 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.105 |
| Scholarly communication | 0.015 | 0.025 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.007 | 0.014 |
| 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".