Moral decision-making in the name of society (without expertise)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scott Hershovitz argues that law is a moral practice. In this response, I argue that he is right that we do well to turn our attention to moral questions. However, I argue that Hershovitz should embrace a more thoroughgoing eliminativism, according to which we don't say that law is a moral practice, but rather say nothing at all about law and address the moral questions directly. Hershovitz says that the rule of law requires us to see legal practices as sources of morality. But that requires settling what a ‘legal practice’ is, reproducing questions that more comprehensive eliminativism enables us to avoid. I argue that the rule of law cannot require seeing legal practices as sources of constraint in advance. Instead, we must always determine what is morally required in light of our practices in an all-things-considered assessment. Hershovitz further argues that lawyers are moral experts; I respond that none of us can claim moral expertise, but all of us have the moral responsibility to make our best assessment of what is morally required of us in a given situation, and we cannot rely on ideas of the law or the rule of law to settle that difficult question.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it