Evidence for distinct biodevelopmental influences on male sexual orientation
Bibliographic record
Abstract
Several biological mechanisms have been proposed to influence male sexual orientation, but the extent to which these mechanisms cooccur is unclear. Putative markers of biological processes are often used to evaluate the biological basis of male sexual orientation, including fraternal birth order, handedness, and familiality of same-sex sexual orientation; these biomarkers are proxies for immunological, endocrine, and genetic mechanisms. Here, we used latent profile analysis (LPA) to assess whether these biomarkers cluster within the same individuals or are present in different subgroups of nonheterosexual men. LPA defined four profiles of men based on these biomarkers: 1) A subgroup who did not have these biomarkers, 2) fraternal birth order, 3) handedness, and 4) familiality. While the majority of both heterosexual and nonheterosexual men were grouped in the profile that did not have any biomarker, the three profiles associated with a biomarker were composed primarily of nonheterosexual men. We then evaluated whether these subgroups differed on measures of gender nonconformity and personality that reliably show male sexual orientation differences. The subgroup without biomarkers was the most gender-conforming whereas the fraternal birth order subgroup was the most female-typical and agreeable, compared with the other profiles. Together, these findings suggest there are multiple distinct biodevelopmental pathways influencing same-sex sexual orientation in men.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".