"The Self-Preference Principle: Benthamâs Transition to Epistemological and Democratic Radicalism"
Bibliographic record
Abstract
A longstanding challenge of Bentham scholarship has been to explain when and how when Bentham was radicalized and became a democrat.A long line of Bentham scholars from Halevy through Mack and Burns to Dinwiddy, Rosen and Schofield, have addressed the issue and contributed one way or another to what will eventually be a successful solution.I will not review the history at this time, but in light of Philip Schofield's recent study of Bentham's transition to radicalism, Utility and Democracy: the Political Thought of Jeremy Bentham 1 , I will offer a summary of my view of the transition that I hope will be useful.Firstly, however, let me say that Schofield's book is in many ways an excellent one for which he is to be thanked by all interested in Bentham.It is very scholarly, informative
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".