Stepping up as an essential service: grocery retailing and the COVID-19 pandemic in Canada
Bibliographic record
Abstract
The COVID-19 pandemic has elevated the ‘essential service’ question to the forefront of government policy, business functioning, and public discourse. This qualitative study uses community disaster resilience and institutional work theory to analyse the responses of Canadian grocery retailers to COVID-19. Based on a thematic analysis of 53 grocery retailers’ website messaging over three periods at the height of the first wave of the COVID-19 pandemic in Canada, the research identifies ten themes that capture the retailers’ response to the pandemic. Focusing on major grocery retailers in Ontario, the research tracks messaging concerning the elevated community role of grocery retailers through a period of crisis. We develop a conceptual framework to understand the community disaster resilience levers of grocery retailing during a pandemic. The research highlights the shift in the balance of messaging concerning the institutional logic of grocery retailers, away from market forces towards a community logic. The findings illustrate how grocery retailers stepped up as an essential service and extended their reach beyond the bounds of their underlying institutional logic to encompass the public good.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".