The nature of incoming graduate social work students' attitudes toward sexual minorities
Bibliographic record
Abstract
Competent social work practice with sexual minorities requires educators to identify factors that can be addressed in the graduate social work curriculum to foster affirming attitudes among students. This study explored the attitudes incoming master of social work (MSW) students hold toward sexual minorities, utilizing a scale that addresses contemporary subtle biases toward lesbian, gay, and bisexual (LGB) people, rather than overt, fear- and morality-based objections measured in previous studies. We explored the role of race/ethnicity, age, sex, sexual orientation, religiosity, political ideology, perceived biological causation of sexual orientation, and LGB social contacts on students' attitudes toward sexual minorities. Multivariable linear regression results suggest that being African American/Black (versus White), older, and heterosexual (versus sexual minority), and greater religiosity (importance of religion and frequency of service attendance) and conservative political ideology, predicted less affirming attitudes, while greater endorsement for genetic causation of sexual orientation and exposure to LGB friends and immediate family members each predicted more affirming attitudes among our sample.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".