Old Country Passions: An International Examination of Country Image, Animosity, and Affinity among Ethnic Consumers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 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 it