Limitations to the use of secondary sex characteristics for gender comparisons
Bibliographic record
Abstract
BACKGROUND: To control for the confounding effect of maturation many researchers use secondary sex characteristics to compare individuals within and between genders. However, this assumption presumes that the timing and tempo of secondary sex characteristics is identical in both genders. AIM: The study investigated the timing and relationships between sexual and somatic maturation indices between and within genders. SUBJECTS AND METHODS: Eighty three boys and 75 girls, aged between 8 and 15 years at study entry, were measured every 6 months for 6 consecutive years. Sexual maturation was assessed through pubic hair, facial hair and axillary hair development in boys, and pubic hair development and menarcheal status in girls. Somatic maturation was assessed through age at peak height velocity (PHV). RESULTS: Low to moderate correlations (r = 0.30-0.55, p < 0.05) existed between age of PHV and age of reaching each pubic hair stage. The majority of boys reached PHV in pubic hair stage 4 (79.2%). The majority of girls reached PHV in pubic hair stage 3 (42.5%) and pubic hair stage 4 (47.5%). CONCLUSION: Boys and girls differ in the timing and tempo of somatic and sexual maturity. Thus boys and girls should not be aligned on secondary sex characteristics when controlling for the confounding effects of maturity.
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 | 0.193 | 0.433 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".