What does ‘buying local’ mean to wine consumers?
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
This study sought to understand what buying ‘local’ means to Ontario wine consumers and determine how local wine purchase behaviour varies with select demographic and environmental belief factors. Few studies concerning the perception of and reasons for purchasing local wine have been conducted, and none in the context of Ontario wine consumers. An online survey of Ontario wine consumers (N = 521) was carried out and results showed that perceptions of localness differed between food products (‘coming from within a 100 km radius of home’) and wine (‘coming from anyway in North America and Canada’). The most important motivational factors reported for purchasing local wine were directly linked to economic and hedonic factors, specifically; ‘support local vineyards and wineries’, ‘build the local economy’ and ‘taste and flavour’. High frequency purchasers of local wines also bought local foods more often and were more likely to seek information about the origin of their food than were lower frequency purchasers. A pro-ecological worldview is associated with higher purchasing frequency of Ontario wine. These results can assist Ontario wineries with respect to market segmentation and development of campaigns focused on local wine.
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 | 0.004 | 0.000 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it