Infant male circumcision and the autonomy of the child: two ethical questions
Bibliographic record
Abstract
Routine neonatal circumcision--the non-therapeutic circumcision of infant males--has generated considerable ethical controversy. In this article, I suggest that much of the disagreement results from conflicting ideas about the autonomy of the child. I examine two questions about autonomy. First, I ask whether we should be realists or idealists about the future autonomous choices of the child-that is, whether we should account for the fact that the child may not make the best choices in future, or whether we should assume that his future choices will reflect his best interests. Second, I ask whether the child has a right to autonomy with respect to circumcision, an interest in autonomy or neither--that is, whether respect for autonomy overrides considerations of interests, whether it counts as one interest among many or whether it counts for nothing. In response to the first question, I argue that we should be idealists when evaluating the child's own interests, but realists when evaluating public health justifications for circumcision. In response to the second question, I argue that the child has an interest in deciding whether or not to be circumcised, insofar as the decision is more likely to reflect his actual interests and his own values. Finally, I show how these findings may help to resolve some particular disputes over the ethics of infant male 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".