Grocery Experience Survey: A Canadian Perspective on Service, Product and Management Specifies
Bibliographic record
Abstract
The socio-economic significance of independent grocers has been, for the most part, underappreciated and overlooked for several decades in the Western world. Few studies have been looked at the field in recent years and even less so in Canada. Retail studies have highlighted the sector’s evolution, particularly the emergence of multiple channel designs. The primary focus of previous studies has been on food retailing, but not ownership and localized market adaptation. This study intended to identify the limitations of our knowledge related to independent grocers in Canada. By using our study’s outcome and identifying key drivers for market adaptation, this study aspires to highlight their somewhat subordinate relationship to government and the difficulties of modernising their business methods. Results show that Canadians regularly visit 2.3 grocery stores on average, 1.29 times a moth for an average duration of 32 minutes. Results also show that service specificity, and to a certain extent, product specificity can provide independent grocers with an advantage. While most consumers value receiving assistance when needed, younger consumers appreciate knowing who works at the grocery store they visit. Trust on ownership is also key in management specificity. This study provides a platform for future research on independently own grocers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".