Can a Naturally Occurring Pathogen Threat Change Social Attitudes? Evaluations of Gay Men and Lesbians During the 2014 Ebola Epidemic
Bibliographic record
Abstract
Previous evidence linking disease threat and social attitudes suggests that a highly salient society-wide pathogen threat should lead to more negative attitudes toward gay men and lesbians. Using a sample of 248,922 Americans recruited via the Project Implicit website, we tested whether implicit attitudes toward gay men and lesbians shifted as a result of the 2014 Ebola virus outbreak. Regression discontinuity analyses, but not t-tests, showed evidence of a small shift in implicit (but not explicit) attitudes at the height of public concern over Ebola. These results could be interpreted as providing partial support for the effects of naturally occurring pathogen threats on social attitudes. Alternatively, given the large size of our sample, the mixed evidence and small effects may reflect a boundary condition for the operation of the behavioral immune system.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".