Bibliographic record
Abstract
Countries worldwide are increasingly expanding male/female binary sex classifications to recognize a third status. Intersex newborns may be included in this third category on birth certification. Parents, families, and communities require counselling and education to accommodate intersex newborns without stigma or discrimination. Whatever its biological or genetic origin, intersex status is a natural if relatively uncommon condition (one in 1500-2000 live births) that distinguishes sex from gender. The tendency of societies to recognize only male and female genders at birth has resulted in intersex children being subjected to invasive surgery and related, sometimes lifelong, medication to confirm them as male or female. On gaining maturity, some are severely distressed and resentful that early gender assignment was mistaken, particularly when excision of testes to enforce femininity or of ovaries to enforce masculinity has denied them procreative capacity. Emerging principles support postponement of such interventions until intersex individuals can make a gender choice 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 | 0.025 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".