Validation of the Brief Perceived Sexual Minority Discrimination Questionnaire-Community Version
Bibliographic record
Abstract
Sexual minorities—people who identify as lesbian, gay, bisexual, etc.—experience unique forms of discrimination. Yet few validated measures assess sexual minority discrimination, and none allow for comparison with other forms of discrimination. I examined an adaption of the Brief Perceived Ethnic Discrimination Questionnaire-Community Version (PEDQ-CVB) for use with sexual minorities (PSMDQ-CVB). Sexual minority participants complete the PSMDQ-CVB online in addition to measures of harassment, sexual minority identity, and well-being (N = 528). Exploratory factor analysis found that the PSMDQ-CVB's factor structure was inconsistent with the four-factor structure of the original PEDQ-CVB. The 16 items retained had strong internal consistency, and good convergent validity with measures of sexual minority discrimination. The PSMDQ-CVB had good divergent validity with measures of stressful life events, and sexual minority identity, and good predictive validity with well-being measures related to discrimination: symptoms of depression, anxiety, and physical ill-being. Results support the psychometric validity of the PSMDQ-CVB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".