The influence of culture on consumer perceptions of deceptiveness
Bibliographic record
Abstract
Purpose This study aims to apply McCornack’s (1992) information manipulation theory to the context of fraud and investigates the effects of culture on perceived deceptiveness. Design/methodology/approach In total, 400 Chinese consumers and an equal-size sample of Canadian consumers were recruited to fill an online survey. The survey integrates four scenarios of insurance fraud and measures of perceived deceptiveness, cultural tightness and horizontal-vertical idiocentrism allocentrism, in addition to some control variables. Findings Results show that at the societal level of culture, perceived deceptiveness is higher in individualistic than in collectivistic cultures. When accounting for the level of situational constraint, cultural tightness was found to magnify the perceived deceptiveness. At the individual level of culture, vertical-allocentrism and vertical-idiocentrism were found to weigh against the perception of deceptiveness. Originality/value Understanding cultural differences in perceived deceptiveness is helpful to spot sources of consumers’ vulnerability to fraud tolerance among a culturally diverse public.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".