Same-sex marriage legalization associated with reduced implicit and explicit antigay bias
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current research tested whether the passing of government legislation, signaling the prevailing attitudes of the local majority, was associated with changes in citizens' attitudes. Specifically, with ∼1 million responses over a 12-y window, we tested whether state-by-state same-sex marriage legislation was associated with decreases in antigay implicit and explicit bias. Results across five operationalizations consistently provide support for this possibility. Both implicit and explicit bias were decreasing before same-sex marriage legalization, but decreased at a sharper rate following legalization. Moderating this effect was whether states passed legislation locally. Although states passing legislation experienced a greater decrease in bias following legislation, states that never passed legislation demonstrated increased antigay bias following federal legalization. Our work highlights how government legislation can inform individuals' attitudes, even when these attitudes may be deeply entrenched and socially and politically volatile.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it