Consumer Perceptions about the Value of Short Food Supply Chains during COVID-19: Atlantic Canada Perspective
Bibliographic record
Abstract
The recent global COVID-19 pandemic has revealed weaknesses in the global food system, with short food supply chains (SFSCs) and long food supply chains (LFSC) being impacted differently. This raises the question as to whether the pandemic has contributed to a greater interest in and demand for locally produced foods. To answer this question, a study was undertaken to explore how consumers perceive SFSCs in delivering social, economic, and environmental benefits and whether these perceptions have been enhanced during the pandemic. A survey was carried out among consumers in Atlantic Canada who purchase food from SFSCs. Based on 80 valid responses, the findings revealed that consumers perceive SFSCs to deliver more social benefits post-pandemic than they thought SFSCs did before the pandemic. Supporting the local economy, food safety, freshness, and product quality are key motivators of shopping from SFSCs. Consumer perceptions about the sustainability of SFSCs did not vary much based on sociodemographic factors. Also, the COVID-19 pandemic did not significantly alter consumer spending and frequency of shopping from SFSCs. This may affect the SFSCs’ ability to expand operations beyond current levels and suggest the complementarity between SFSCs and LFSCs for more sustainable consumption patterns. The study provides valuable insights into the attractiveness of the local food businesses and the effect of unexpected events such as COVID-19 on consumer behaviors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".