An empirical study of the magnitude and sources of consumer confusion about the company of origin of consumer packaged goods
Bibliographic record
Abstract
The present study was an exploratory investigation of the consumer confusion about the company of origin of consumer packaged goods. It examined the magnitude and potential sources of consumer confusion about the company of origin in selected consumer packaged goods and identified the extent of normal consumer confusion. The research was conducted in Guelph and Cambridge, Canada. The product categories were shampoo/conditioner and multivitamin products. Two studies were conducted. Study One measured consumer confusion about the company of origin of products and consumer individual characteristics, which may be the potential sources of such confusion. Study Two measured similarity in appearance/names between selected product alternatives in each category. Results from both studies were combined in the final stage to explore relationships between the potential sources and consumer confusion about the company of origin of products and to gauge the extent of normal consumer confusion. Both studies used mall intercept techniques and standardized survey instruments. The study results revealed very low confusion rates and weak relationships between the proposed sources and consumer confusion about the company of origin of products. Theoretical and methodological implications of the results were discussed as well.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".