Unpacking Cultural Variations in Social Anxiety and the Offensive-Type of Taijin Kyofusho Through the Indirect Effects of Intolerance of Uncertainty and Self-Construals
Bibliographic record
Abstract
This article presents two studies that aim to unpack cultural variations in general social anxiety (SA) and the offensive-type of Taijin Kyofusho (OTKS)—a type of SA characterized by the extreme fear of offending others. Cultural variations in the expression and manifestation of SA are well established; however, the mechanisms underpinning this relation are unclear. The present studies use the Parallel Multiple Mediation Model to study how SA and OTKS are jointly shaped by self-construal and intolerance of uncertainty (IU). Study 1 compared Euro-Canadians and Chinese migrants in Canada. Results showed a mean group difference in OTKS, but not SA, with the difference mediated by IU. Study 2 tested this pattern of multiple mediations in Japanese, Chinese, and Euro-Canadian cultural contexts. Results showed significant differences among these three cultural groups on both SA and OTKS via multiple mediators (e.g., independent vs. interdependent self-construals and IU). Findings in both studies revealed that OTKS seems to be a psychopathology that is not specific to Japanese participants. The underlying mechanisms and processes of OTKS are also significantly different from SA. Significant cultural variations in SA and OTKS between Chinese versus Japanese cultural contexts were observed in Study 2. These studies demonstrate the conceptual and empirical advantages of using more complex models to unpack the psychological mechanisms shaping cultural variations in SA and OTKS.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".