Culture and decision‐making: Investigating cultural variations in the <scp>E</scp>ast <scp>A</scp>sian and <scp>N</scp>orth <scp>A</scp>merican online decision‐making processes
Bibliographic record
Abstract
Research in cross‐cultural psychology suggests that East Asians hold holistic thinking styles whereas North Americans hold analytic thinking styles. The present study examines the influence of cultural thinking styles on the online decision‐making processes for Hong Kong Chinese and European Canadians, with and without time constraints. We investigated the online decision‐making processes in terms of (1) information search speed, (2) quantity of information used, and (3) type of information used. Results show that, without time constraints, Hong Kong Chinese, compared to European Canadians, spent less time on decisions and parsed through information more efficiently, and Hong Kong Chinese attended to both important and less important information, whereas European Canadians selectively focused on important information. No cultural differences were found in the quantity of information used. When under time constraints, all cultural variations disappeared. The dynamics of cultural differences and similarities in decision‐making 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".