Measurement invariance of the <scp>LGBT</scp> People of Color Microaggressions Scale among <scp>LGBTQ</scp>+ youth
Bibliographic record
Abstract
The LGBT People of Color Microaggressions Scale (LGBT-PCMS) is a widely used measure of intersectional microaggression experiences among sexual and gender minority people of color. Although it is widely used-and increasingly used in adolescent and young adult samples-it is unknown whether the LGBT-PCMS demonstrates similar measurement properties across subgroups of sexual and gender minority youth of color (SGMYOC). Among 4142 SGMYOC (ages 13-17) we found evidence for either partial or full scalar invariance (item loadings and intercepts were generally equal) across sexual orientation, race-ethnicity, and gender identity groups for all three subscales. Specific patterns of invariance and noninvariance across groups, as well as implications for the use of the LGBT-PCMS and its subscales among SGMYOC are discussed.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".