Factors influencing food-buying practices of grocery shoppers in London, Ontario.
Bibliographic record
Abstract
We need to understand better the reasons why people choose to buy the foods that they do. The main objective of this study was to obtain information on some of the factors that influence food-buying practices of grocery shoppers in London, Ontario. For this study, a copy of Canada's Food Guide to Healthy Eating tearsheet and a self-administered seven-item postcard-style questionnaire were distributed to 2,000 grocery shoppers in ten London A&P supermarkets; 29% of receptive shoppers (572 of 2,000) completed the survey. Grocery shoppers indicated that price, freshness and health considerations were the top three factors considered important when buying food. Average food expenditure for a family of three was approximately $103 per week. A majority of respondents (55%) wanted more information on healthy food choices. The results may provide information for health educators to understand better the factors that influence grocery shoppers food-buying practices. Knowledge of these factors may also help health educators design nutrition information and health promotion interventions at point-of-purchase outlets that could be aimed at influencing more grocery shoppers to take steps toward healthier food-buying behaviours.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".