How Did Food Acquisition Patterns Evolve During the Course of the <scp>COVID</scp> ‐19 Pandemic? An International Study During 2021, 2022, and 2023
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT The COVID‐19 pandemic compelled governments to implement various stringent measures, causing changes in food consumption patterns. In this study, we examine changes in consumer behaviors such as online grocery shopping and restaurant dine‐in/takeouts in the United States, Canada, France, the United Kingdom, South Korea, and Japan from 2021 to 2023 using multivariate probit regressions. The results reveal that food acquisition behaviors are shaped by a complex interplay of risk perceptions, socio‐demographic characteristics, and changing pandemic phases. Our study offers insights for food business marketing strategies and provides information for stakeholders in the international agribusiness industry through a multi‐country comparison.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it