Identity salience moderates the effect of social dominance orientation on COVID-19 ‘rule bending’
Bibliographic record
Abstract
Amidst the economic, political, and social turmoil caused by the COVID-19 pandemic, contrasting responses to government mandated and recommended mitigation strategies have posed many challenges for governments as they seek to persuade individuals to adhere to prevention guidelines. Much research has subsequently examined the tendency of individuals to either follow (or not) such guidelines, and yet a ‘grey area’ also exists wherein many rules are subject to individual interpretation. In a large study of Canadians (N = 1032, Mage = 34.39, 52% female; collected April 6, 2020), we examine how social dominance orientation (SDO) as an individual difference predicts individual propensity to ‘bend the rules’ (i.e., engaging in behaviors that push the boundaries of adherence), finding that SDO is significantly and positively associated with greater intentions toward rule-bending behaviors. We further find that highlighting a self-oriented or in-group identity enhances the relationship between SDO and rule-bending, whereas making salient a superordinate-level identity (e.g., Canada) attenuates this effect. Implications for theory and practice are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".