Produce Retail Price Volatility and Perceptions in the Canadian Market: Nutrition Security Variances
Bibliographic record
Abstract
Nutrition security has been studied but rarely in the context of a developed economy. Furthermore, few studies have looked at how fluctuating produce process may influence nutrition security and how consumers cope with abrupt macro-economic changes. Between 2014 and 2015, Canadian consumers saw produce prices jump by more than 25% in a year in some cases. This exploratory survey looks at socioeconomic factors and evaluates how price increases influence produce consumption and substitution. A total of 1007 respondents participated in a cross national survey over a two-week period. Results show that lower income households are more vulnerable than higher income respondents. Results also explore a few more behavioral factors such as where produce shopping occurs and how market data is gathered before purchases. Respondents who consult flyers and use apps are more likely to behave rationally and cope with changing prices. Some limitations are presented. And finally, future research thrusts related to produce price fluctuations and nutrition security are suggested.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 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 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".