Bad news: do reminders of mortality influence support for authoritarian attitudes and social policies?
Bibliographic record
Abstract
Terror management theory predicts that when people are reminded of their own mortality (mortality salience), they cling more strongly to cultural worldviews which provide them with a sense of security (Greenberg et al., 1986). For some people, this reaction to mortality salience also involves derogation of, and discrimination against, “other” people and cultures. An increasing tendency towards sensationalism in the news media has resulted in even more frequent reminders of vulnerability and death (e.g., terrorism, violent crime, health and safety concerns). In two experiments involving 868 introductory psychology students, the present research examined the extent to which their (a) support for authoritarian social policies relevant to Canada and (b) authoritarian attitudes in general are influenced by mortality salience. Specifically, right-wing authoritarianism, attachment security, and political orientation were measured in participants in both experiments. Participants were then prompted to think about either their own mortality or about another aversive experience having nothing to do with mortality. Next, participants were asked their opinions regarding authoritarian social policies (Experiment 1) and beliefs indicative of right-wing authoritarianism (Experiment 2). Multiple regression, analysis of variance, and t-tests revealed that individuals with (a) high pre-existing right-wing authoritarian attitudes and (b) conservative political beliefs increased their support for authoritarian social policies following mortality salience (Experiment 1). In contrast, individuals with (a) high attachment security and (b) moderate political beliefs decreased their support for right-wing authoritarian beliefs following mortality salience (Experiment 2), although the former relationship only approached statistical significance. The findings are discussed in terms of their implications for the news media, for social policies and political opinions, and for social justice.
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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 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".