Bibliographic record
Abstract
Janet Semple wrote that Panopticon was the only book by Jeremy Bentham that Michel Foucault had ever read. It follows that Bentham scholars have considered Foucault’s Discipline and Punish as both a critical and an incomplete analysis of Bentham’s thought. The recent 2004 edition of Foucault’s unpublished lectures at the College de France and the 2006 seminal paper by Christian Laval, a French Bentham scholar from the Centre Bentham, give grounds for reappraising received ideas on the relationship between Foucault and Bentham. Foucault’s understanding of Bentham clearly goes beyond concepts of surveillance to focus on the idea of governance; the latter is more in tune with contemporary Bentham studies. Concepts used by Foucault in his lectures, such as that of ‘frugal/frugality’ not only derive from Bentham’s writings but are more relevant to an analysis of Bentham’s philosophy than the corresponding concept ‘economical/economy’ used by contemporary scholars. Over the years, Foucault seems to have moved on from an incomplete and therefore inaccurate knowledge of Bentham to a deeper understanding of his work. This paper not only challenges Bentham scholars’ prejudices against Foucault’s analysis but also aims at overcoming received ideas about Bentham’s philosophy among the French academic community.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.041 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".