Development and Validation of a Scale Measuring Modern Prejudice Toward Gay Men and Lesbian Women
Bibliographic record
Abstract
This paper describes the psychometric properties of the Modern Homonegativity Scale (MHS), which measures contemporary negative attitudes toward gay men and lesbians (i.e., attitudes not based on traditional or moral objections to homosexuality). In Study 1 (N = 353), a preliminary version of the MHS was developed, and its psychometric properties were examined. Participants in Studies 2 and 3 (Ns = 308 and 233, respectively) completed the MHS and other attitudinal measures. The relationships among these variables were investigated to provide a more comprehensive assessment of the scale's construct validity. In Study 4 (N = 36), a behavioural expression of modern homonegativity was examined using the attributional ambiguity paradigm. The results of these studies indicate that the MHS is unidimensional, possesses a high degree of internal consistency, and is factorially distinct from a measure of old-fashioned homonegativity. As hypothesized, scores on the MHS correlated positively with political conservatism, religious behaviour, religious self-schema and modern sexism, but did not correlate significantly with social desirability bias. In addition, the MHS appears to be less susceptible to floor effects than a commonly used measure of old-fashioned homonegativity. Finally, the experimental study revealed that participants obtaining high scores on the MHS were less likely to sit beside individuals wearing T-shirts with pro-gay or pro-lesbian slogans when they could justify their seating choice on nonprejudicial grounds.
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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 | 0.013 | 0.019 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".