Bibliographic record
Abstract
Sex-change procedures, better described as gender-change procedures, involve preparing patients psychologically and surgically for gender transition to treat their gender dysphoria. Physical treatment might include hysterectomy for female to male transition, and post-castration fashioning of an artificial vagina for male to female transition. Conservative opposition to accommodating and recognizing such procedures remains in some countries, and where treated, transgender individuals might face social hostility and oppression. However, human rights laws increasingly provide for transgender non-discrimination and government re-issue of official documents such as birth certificates and social insurance cards in the changed gender. A UK legal decision required a transgendered male who retained his ovaries and uterus to be registered as mother on the birth certificate of the child he bore. Most challenging are decisions on adolescents' requests for gender transition, especially over parents' objections. Laws increasingly recognize that legal minors with sufficiently evolved intellectual and emotional capacity can make decisions for themselves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.073 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.060 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.018 | 0.037 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".