The Assessment of Quantity, Diversity and Quality of CSR Reports in Canadian Food Retailing: A Comparative Study Among and Between Retailers Using Content Analysis
Bibliographic record
Abstract
This content analysis study assesses the corporate social responsibility (CSR) reports of Canada’s top food retailers for quantity, diversity and quality. Given a responsibility for food retailers to be accountable in how they operate their business, CSR reporting is the retailer’s way of publicly disclosing their social and environmental operations. Although previous studies have looked at the CSR of food retailers, none has investigated Canadian retailers. This study uses a modified consolidated narrative interrogation (CONI) method (Beck et al., 2010). Key results include that CSR reports contain higher Quantity Indices related to the social dimension than the environmental dimension, larger retailers overall display higher Diversity and Quality Indices than smaller retailers, and retailers report on the same CSR topics due to having shared stakeholders. The results of the study also indicate there is room for improvement in the quality and diversity of CSR reports, and quantity, diversity, and quality of CSR reports have a wide variation.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".