Ideologically‐based contact avoidance during a pandemic: Blunt or selective distancing from ‘others’?
Bibliographic record
Abstract
Abstract This project sought to understand when ideology is relevant (or not) to predicting contact avoidance of ‘others’ during the COVID‐19 pandemic. Right‐leaning ideologies (political conservatism, right‐wing authoritarianism, social dominance orientation) were not expected to predict greater contact avoidance per se, but rather exhibit selective avoidance of outgroup (vs. ingroup) members. White British participated in one exploratory (Study 1 N = 364) and two pre‐registered (Study 2 N = 431, Study 3 N = 700) studies. As expected, right‐leaning ideologies were significantly stronger predictors of greater preferred personal distance and contact discomfort regarding foreign outgroups (vs. British ingroup) in Studies 1 and 3 (partially supported in Study 2). Ideology rarely predicted ingroup reactions. This Ideology × Target pattern was itself not moderated by the perceived COVID‐19 threat. Pre‐pandemic theorizing that heightened behavioural immune system responses are associated with heightened right‐leaning ideologies appear insufficient for use in actual pandemic contexts, especially when highly politicized.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".