Old Country Passions: An International Examination of Country Image, Animosity, and Affinity among Ethnic Consumers
Bibliographic record
Abstract
Ethnic consumers are an important market segment in both traditionally multicultural countries and newer destinations of growing immigration waves. Such consumers may carry with them “old country passions” that may influence their attitudes toward the products of countries perceived as friendly or hostile in relation to the consumers’ original home countries. This study is the first to examine together four place-related constructs—namely, country and people images, product images, affinity, and animosity—and their potential effects on purchase intentions for products from countries that may be perceived as friends or foes from the perspective of the ethnic consumers’ homeland, while also juxtaposing these measures against views toward a neutral “benchmark” country for comparison. The results show that country/people and product images, affinity, and animosity work differently depending on the target country; both affective and cognitive factors influence product and people evaluations; and attitudes vary in their predictive ability on purchase intentions. The article concludes with a discussion implications from the findings and directions for further research.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".