The terror management effects of a disaster song
Bibliographic record
Abstract
Following terror management theory (TMT), we hypothesized that listening to a disaster song could increase cultural worldview defenses in a manner similar to the mortality-stimulating essay typically used in TMT research. Participants were divided into four groups. Two of the groups received death-related themes: one wrote an essay about dying and the other group heard a song about men who died in a shipwreck. The other two groups received pain-related stimuli: one wrote an essay about dental pain and the other heard a song about a migrant worker’s painful separation from family. Dependent variables examined pro-social behavior, ranking one’s country, children, and emotions. Results showed similar effects for the mortality-stimulating essay and the disaster song on two variables: ranking one’s country in the world and the importance of having children. In addition, compared to the pain-of-separation song, the disaster song produced significantly more negative and less positive emotion ratings; the emotion ratings of the essay groups did not differ significantly. Results show that a disaster song can produce effects similar to those that have been observed for a mortality-stimulating essay. Further, the effects of disaster songs may extend to strengthening cultural worldview defenses.
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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 | 0.000 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".