COVID-19 Increased Mortality Salience, Collectivism, and Subsistence Activities: A Theory-Driven Analysis of Online Adaptation in the United States, Indonesia, Mexico, and Japan
Bibliographic record
Abstract
How does a life-threatening pandemic affect a culture? The Theory of Social Change, Cultural Evolution, and Human Development predicts that danger, as indicated by rising death rates and narrowing social worlds, shifts human psychology and behavior toward that found in small-scale, collectivistic, and rural subsistence ecologies. In particular, mortality salience, collectivism, and engagement in subsistence activities should increase as death rates rise and the social world retracts. Studies on the psychological response to the pandemic in the United States confirmed these predicted increases. The present study sought to generalize these previous findings by comparing the frequency of conceptually relevant linguistic terms used in Google searches and Twitter posts in the United States, Japan, Indonesia, and Mexico for 30 days before the coronavirus pandemic began in each country with frequencies of the same terms for 30 days after. Generally, we found that mortality salience increased to the extent that countries experienced excess COVID mortality; collectivism increased to the extent that countries experienced excess COVID mortality and increased mortality salience; and subsistence activities increased to the extent that countries experienced excess COVID mortality and/or stay-at-home-policies. Almost all these increases went beyond the general increase in internet use, which was a control variable in all analyses. These findings support a growing body of research documenting a human response to ecological danger.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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; 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".