The complex representation and contradicting results linking sexual orientation to allostatic load
Bibliographic record
Abstract
This commentary discusses a publication by Katsuya Oi and Amanda M. Pollitt using the National Longitudinal Study of Adolescent to Adult Health to assess presumed sexual orientation effects on allostatic load, the 'wear and tear' of chronic stress. Their findings indicate that discordant heterosexual women-those whose sexual attractions or behaviors do not align with their heterosexual identity-experience notably higher allostatic load compared to other sub-groups. In contrast, women who identify as non-heterosexual did not exhibit significantly elevated allostatic load. Several theoretical problems, interpretative inadequacies, issues with terminology, and misrepresentation of the existing literature limit the full impact of this original work. In the spirit of collegial critique, the objective of this commentary is to offer potential resolutions and considerations for future research among sexually diverse as well as gender diverse populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".