Development and validation of the Positive Bisexual Identity (PBI) scale
Bibliographic record
Abstract
Positive sexual minority identity is a vital point of investigation for bisexual individuals. However, no measure currently exists that specifically examines positive sexual identity in bisexual people, whose experiences differ from those of gay men and lesbian women. These three studies outline the development, refinement, and validation of a measure of positive bisexual identity. In Study 1, participants completed an initial pool of items and a validation measure. A principal component analysis (PCA) was conducted for item reduction. Studies 2 and 3 investigated the Positive Bisexual Identity (PBI) measure’s scale-score reliability and dimensionality using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The construct validity of the PBI scale also was tested using measures expected to correlate with positive bisexual identity. Cronbach’s alpha coefficients and Omega coefficients provided support for scale score reliability, and the proposed nomological network offered support for the PBI’s construct validity. Our findings elucidate potential differences between positive bisexual identity and positive gay/lesbian identity. The PBI has potential as a scale that can be used to measure positive bisexual identity in both research and clinical settings.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".