Reaction to norm transgressions and Islamization threat in culturally tight and loose contexts: a cross-cultural comparison of Germany versus Russia
Bibliographic record
Abstract
Prior research shows that North Americans and Western Europeans react to threats with defensive strategies based on behavioral approach vs. inhibition systems (BAS/BIS)-i.e., a desire to approach a goal or to avoid a threat. In the present research, we explored whether this phenomenon is more pronounced in tight cultures (e.g., Germany) as compared to loose cultures (e.g., Russia), testing how Germans and Russians respond to societal threats. We expected that due to the higher levels of cultural tightness, Germans would show stronger defensive reactions to threats than Russians. Additionally, we investigated the role of need for tightness (i.e., need for strict regulation of social order) in threat management processes. In Study 1, Germans recalling violations of societal norms produced stronger rightward bias on the line bisection task than Russians, indicative of greater BAS activation in Germans than in Russians. In Study 2, we used frontal alpha asymmetry, providing the first cross-cultural test of BIS-BAS reactions utilizing neuronal markers. In this study, presentation of societal threat in a video portraying Islamic immigration as a large-scale violation of social norms led to higher BIS activation among Germans than among Russians, if their need for tightness was high. We discuss the role of tightness, need for tightness, and type of threat for cross-cultural particularities of threat-induced motivational shifts.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".