Measuring retailers' commitment toward regional foods: the CIBLE‐Chaire Bombardier Index
Bibliographic record
Abstract
Purpose This paper aims to present the methodology used to develop an index for assessing retailers' efforts to promote regional foods, and to provide an analysis of the evaluation of 278 retailers. Design/methodology/approach A three‐step procedure was used to develop the index. First, the dimensions of the index were identified through a literature review and interviews with retailers. Next, face‐to‐face interviews with retailers, food producers and regional development experts were conducted to define the best way to measure the index dimensions. Finally, a Delphi approach with an expert panel was used to determine the relative importance of the dimensions. The index was used to evaluate 278 food retailers from the province of Quebec in Canada. Data collection was conducted through store observation and interviews with managers or owners. Findings The results reveal a weak level of commitment toward regional foods. Only a small group of retailers, 16 per cent of the sample analysed, adopted practices that demonstrated commitment toward regional foods. A lower level of commitment was observed among corporate stores and discount supermarkets. Research limitations/implications The index provides an overview of retailers' level of commitment toward regional foods within a region. It is simple to use and the results are easy to communicate. However, further research is needed to validate the index dimensions and their relative importance. Originality/value This is the first study to provide a means of measuring retailers' commitment toward regional foods based on their behaviour.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".