Peer Reviewed: Improving Fruit and Vegetable Consumption: Use of Farm-to-Consumer Venues Among US Adults
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
Improvements to the food environment including new store development and more farm-to-consumer approaches (ie, farmers' markets, roadside stands, pick-your-own produce farms, or community-supported agriculture programs) may aid Americans in making healthier dietary choices. We analyzed data from a subset of respondents (N = 1,994) in the National Cancer Institute's Food Attitudes and Behaviors Survey, a mail survey of US adults. We determined associations between primary grocery shoppers' region and sociodemographic characteristics and frequency of purchasing fruits and vegetables in the summer from farm-to-consumer venues. A little more than one-quarter (27%) of grocery shoppers reported a frequency of at least weekly use of farm-to-consumer approaches. Older adults and respondents who live in the Northeast were most likely to shop farm-to-consumer venues at least weekly, and no differences were found by sex, race/ethnicity, education, or annual household income. These findings suggest that farm-to-consumer venues are used by many Americans and could be expanded to increase access to fruits and vegetables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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