An anthropometric study of sexual orientation and gender identity in Thailand
Bibliographic record
Abstract
The biodevelopment of psychological sex differentiation is putatively reflected in several anthropometrics. We examined eight anthropometrics in 1404 Thai participants varying in sex, sexual orientation, and gender identity/expression: heterosexual men and women, gay men, lesbian women, bisexual women, sao praphet song (transgender birth-assigned males), toms (transgender birth-assigned females), and dees (birth-assigned females attracted to toms). Exploratory factor analyses indicated the biomarkers should be analyzed independently. Using regressions, in birth-assigned males, less male-typical second-to-fourth digit ratios in the left hand were associated with sexual orientation towards men regardless of gender identity/expression, whereas shorter height and long-bone growth in the arms and legs were more evident among sao praphet song-who are both sexually oriented towards men and markedly feminine. In birth-assigned females, there were no clear sexual orientation effects, but there were possible gender-related effects. Groups of individuals who tend to be more masculine (i.e., toms, lesbians) showed more male-typical patterns on weight and leg length than some groups of individuals who tend to be less masculine (i.e., heterosexual women, dees). Thus, it appears the various anthropometrics inform separate biodevelopmental processes that differentially relate to sexual orientation and gender identity/expression depending on the measure in question as well as birth-assigned sex.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".