Culture and Decision: Cross-Cultural Similarities and Variations in Resource Allocation between European Canadians and East Asians
Bibliographic record
Abstract
People engage in a variety of decision making tasks in daily life, in which people’s experiences and strategies during the decision making tasks are affected by cultural influences. The primary objective of this dissertation was to examine the role of analytic versus holistic thinking styles on resource allocation across cultures. Analytic thinking style, which is more prevalent in North America, refers to a linear view about the world where objects’ properties remain stable due to the independent nature of the relationships among objects. In contrast, holistic thinking style, which is more prevalent in East Asia, refers to a non-linear view of how the world is organized in which people perceive change to be a constant phenomenon due to the complex interactions among elements in the universe (Nisbett, Peng, Choi & Norenzayan, 2001). I conducted three cross-cultural studies to understand this phenomenon. Study 1 tested the role of analytic versus holistic thinking styles on people’s resource allocation. Study 2 showed evidence that supported the causal link from cultural thinking styles to decision making experiences in resource allocation. Study 3 examined the role of context-sensitivity, which was found to be higher in East Asian societies than in North American societies, in resource allocation. In Study 1, Hong Kong Chinese, a representative group of holistic cultures, and European Canadians, a representative group of analytic cultures, completed a resource allocation task (i.e., fort game). The results showed that the allocation pattern of European Canadians was more concentrated than that of Hong Kong Chinese. In Study 2, thinking styles were manipulated in which Hong Kong Chinese and European Canadian participants were reminded of either holistic thinking style (by watching a movie showing an nonlinear trend) or analytic thinking style (by watching a movie showing a linear trend). Regardless of cultural backgrounds, the allocation pattern was more concentrated in the analytic condition than in the holistic condition. Finally, the role of context-sensitivity across cultures in resource allocation among Japanese, Hong Kong Chinese and European Canadian participants was examined in Study 3. The results showed that East Asians, especially the Japanese, were more likely to change their resource allocation in a manner consistent with experimental manipulation than European Canadians. Implications of these findings for research using experimental manipulation, cross-cultural research, and applied research are discussed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".