Cultural Differences in the Construal of Suffering and the COVID-19 Pandemic
Bibliographic record
Abstract
The present research examines how suffering is construed across cultures. Study 1 ( N 1 = 264; N 2 = 745) asked participants to provide free associations for suffering. Chinese individuals generated more positive associations than did Euro-Canadians. Study 2 ( N = 522) had participants create a hypothetical potion of suffering to represent what people would experience while suffering. Chinese participants added more positive ingredients and fewer negative ingredients than Euro-Canadians did. How would cultural differences in the construal of suffering matter in a real-life negative situation? Study 3 ( N = 608) showed that Chinese participants generated a greater proportion of potential positive outcomes for the COVID-19 outbreak and reported more positive affect during the pandemic than did Euro-Canadians. Thus, Chinese construe suffering more positively than Euro-Canadians. These findings are consistent with previous research on cultural differences in dialectical thinking and lay theory of change and have implications for coping and resilience.
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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 | 0.000 |
| 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 | 0.006 |
| 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".