Christmas Gift Search Behaviors: A Three-Country Comparison
Bibliographic record
Abstract
ABSTRACT. This study explores the underlying determinants of in-store information search for a Christmas clothing gift, focusing spe-cifically on cross-cultural differences. A self-administered survey, con-taining personality, situational, demographic, and search behavior measures, was distributed to a sample of actual consumers residing in 3 countries: Canada, the United States, and the United Kingdom. Confirmatory fac-tor analysis revealed 3 distinct and reliable in-store search behaviors (macro, micro, and salesclerk help); exploratory factor analyses revealed 23 independent factors (13 personality and 10 situational). Country sam-ple differences were assessed using chi-square tests, ANOVAs, MANCOVAs, multiple regression analyses, and Chow tests. Cross-national differences were found with respect to the relationships/importance of the various search antecedents to in-store search behaviors. Other observed be-Mark Cleveland is a doctoral student in administration at Concordia University,
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".