Contemporary castration: why the modern day eunuch remains invisible
Bibliographic record
Abstract
Let’s study emasculation. No, we don’t mean the loss of political power. That’s a metaphorical sense. We mean the real thing: the removal or chemical destruction of a man’s testes. And here we refer not to the manufacturing of courtiers in Constantinople, nor to the construction of a caste of opera singers, but to modern day emasculations. Although to many people castration signifies a barbarism that disappeared with the demise of the Ottoman empire, the Chinese dynasties, and the castrati movement in European music, there are surely more men living with removed or functionally arrested testes today than at any other time in history. A minority either identify as women and have sex reassignment surgery or sought castration simply to suppress their libidos.1 2 By far the majority, though, are prostate cancer patients, and it’s this group that we focus on here. Chemically shutting down or surgically removing the main source of testosterone—the testes—can slow the spread of prostate cancer. Castration, of course, has extensive side effects.3 A castrated adult male will lose muscle but gain fat.4 He can expect hot flushes like those that women have at menopause.5 He will lose body hair, …
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".