Bibliographic record
Abstract
Legal systems such as those in the United States and Canada, which include fundamental moral rights or provisions in their constitutions, present an interesting and difficult problem for legal positivists. Are such moral standards to count among the existence or validity conditions of laws in those systems, or are they better understood as fundamental objectives or justification conditions which laws may or may not achieve or respect in practice? The first option, known as inclusive legal positivism, expands the traditional positivist separation thesis to mean that although there is no necessary connection between law and morality in general, it is possible that in some systems it is a necessary truth that laws reproduce or satisfy certain demands of morality. The second option, known as exclusive legal positivism, denies this possibility, and maintains instead that it is never a necessary condition that laws reproduce or satisfy certain demands of morality, even if such demands are constitutionally recognized. On the exclusive account, in the context of constitutional states such as the U.S. and Canada, the separation thesis is expanded to mean that there is no necessary connection between the existence and content of laws and the demands of political morality typically included in constitutions. In this paper I defend exclusive positivism and argue that it best follows from traditional positivist commitments and avoids what I take to be a critical problem with inclusive positivism. Further, I argue that the concepts, distinctions, and arguments deployed in the internal positivist debate are also of value in the wider debate between H.L.A. Hart and Ronald Dworkin.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".