Review Of "Engaging Raz: Themes In Normative Philosophy" Edited By A. Marmor, K. Brownlee, And D. Enoch
Bibliographic record
Abstract
From the 1970s until his death in 2022, Joseph Raz shaped more than a generation of thinking regarding jurisprudence, political and moral philosophy, and practical reason. His originality, incisive argumentation, and openness to having his views challenged and developed by others mark him as a highly innovative thinker. In Engaging Raz, editors Marmor (Cornell Univ.), Brownlee (Univ. of British Columbia, Canada), and Enoch (Hebrew Univ., Israel) bring together essays on all these topics and more by 21 highly regarded contemporary philosophers. The essays, each roughly 20 pages or more, are divided into six categories where Raz’s contributions are most significant: "Normativity and Values," "Practical Reasoning," "Agency and Autonomy," "Rights and Obligations," "The Public Domain," and "Authority." Each contributor engages with Raz’s views by challenging them, modifying them, and/or developing them further. This short review cannot do justice to this magnificent collection except to say that it should be on the shelves of all major research institutions and law schools, and read avidly by anyone engaged in any of the subjects listed above. Collections of this sort tend to be uneven; happily, this volume is exceptional as each essay is first-rate. Summing Up: Highly recommended. Graduate students, faculty, and professionals.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".