Predicting Consumers' Acceptability of Pesticide-Free Fresh Produce in Canada's Maritime Provinces
Bibliographic record
Abstract
This study examines consumers' willingness to purchase pesticide-free fresh produce (PFFP) in Canada's Maritime Provinces. Households' decisions in purchasing organic foods are reflected in their willingness-to-pay (WTP) a premium for obtaining these types of products. WTP was modeled as a function of a series of explanatory variables including sociodemographic, socioeconomic, media, and public awareness about the impact of pesticide use on health and environment. Results suggest that Maritimes' consumers tend to pay the premium because they believe that the use of pesticide in conventional farming is life threatening. In addition, males and individuals with bachelor degrees are more willing to pay the premium, but those who visit farmers' markets on a regular basis are less likely to pay a premium for pesticide-free fresh fruit and vegetables. Finally, results show that media have no impact on consumers' decisions to purchase pesticide-free fresh produce.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".