To Bi: An Exploration of Sexual and Romantic Identities, Attractions, and Behaviors
Bibliographic record
Abstract
Research typically measures bisexuality using self-reported sexual identity, attraction, or relationships with men and women. This approach, however, has limitations, including the potential miscategorization of individuals, as well as the exclusion of nonbinary genders and of the romantic dimensions of bisexuality. To better guide research on bisexuality, the current study examined associations between bisexual and biromantic (i.e., bi) identities, and plurisexual and pluriromantic attractions and behaviors among 462 Canadian residents. Participants’ definitions of bisexuality were also analyzed. Results indicated that identities, attractions, and behaviors are related but do not fully overlap. According to logistic regressions, sexual behavior was not a significant predictor of bi identities. Thematic analysis further showed that most bi participants define bisexuality as an attraction to multiple genders/sexes. Together, these findings suggest that future studies should consider the romantic aspects of bisexuality and attraction to nonbinary individuals, while avoiding inferences about bi identities based on behaviors.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".