Ethical Principles for the Management of Infants with Disorders of Sex Development
Bibliographic record
Abstract
The Fifth World Congress on Family Law and Children's Rights (Halifax, August 2009) adopted a resolution endorsing a new set of ethical guidelines for the management of infants and children with disorders of sex development (DSD) [www.lawrights.asn.au/index.php?option = com_content&view = article&id = 76&Itemid = 109]. The ethical principles developed by our group were the basis for the Halifax Resolution. In this paper, we outline these principles and explain their basis. The principles are intended as the ethical foundation for treatment decisions for DSD, especially decisions about type and timing of genital surgery for infants and young children. These principles were formulated by an analytic review of clinician reasoning in particular cases, in relation to established principles of bioethics, in a process consistent with the Rawlsian concept of reflective equilibrium as the method for building ethical theory. The principles we propose are: (1) minimising physical risk to child; (2) minimising psychosocial risk to child; (3) preserving potential for fertility; (4) preserving or promoting capacity to have satisfying sexual relations; (5) leaving options open for the future, and (6) respecting the parents' wishes and beliefs.
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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 | 0.076 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".