Handedness in association with same-sex sexual attraction in Iran
Bibliographic record
Abstract
Previous research has shown that same-sex sexual orientation is associated with differences in handedness. This study investigated this relationship by comparing Iranian cisgender gynephilic males (n = 239), cisgender ambiphilic males (n = 108), cisgender androphilic males (n = 314), transgender androphilic males (n = 103), cisgender androphilic females (n = 250), cisgender ambiphilic females (n = 96), cisgender gynephilic females (n = 32), and transgender gynephilic females (n = 123). Using a modified version of Edinburgh Handedness Inventory, we compared laterality index scores, rates of non-right-handedness, and extreme right-handedness between groups. Also, two features of handedness including its direction (i.e., the dominant hand) and strength (i.e., the degree of variability in preferring one hand over the other) were explored. We found that compared to gynephilic males, cisgender ambiphilic males had elevated non-right-handedness, and cisgender and transgender androphilic males had elevated extreme right-handedness. Our results indicated that right-handed cisgender androphilic males and females had greater strength compared to right-handed cisgender gynephilic males, while right-handed cisgender ambiphilic females and transgender gynephilic females had weaker strength compared to right-handed cisgender androphilic females. This study highlighted the importance of studying handedness direction and strength to understand underlying developmental factors influencing sexual orientation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".