Bibliographic record
Abstract
A number of histories of circumcision have recently been written and in them the case of A. E. Housman, along with a number of others, has acquired a certain prominence. This article reconsiders the existing evidence regarding Housman's circumcision and the various interpretations of it in the secondary literature before going on to examine a number of overlooked sources. While this writing around Housman's circumcision is not without positive results, it will be suggested via a consideration of Jacques Derrida's testimony regarding his own circumcision that the historian of sexuality needs also to contend with an inherent negativity and loss. The testimony provided by a recently uncovered poem on circumcision will prompt the suggestion that we should be wary of overemphasizing the individual example. In conclusion, the article argues that the problematic of Housman's particular case has pertinence because in regard to individual experience we can only ever write around the history of circumcision.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".