Bibliographic record
Abstract
In light of greater attention to the ethical dimensions of consumption and consumer behaviour in recent years, researchers are increasingly excavating the ethical bases of consumer engagement in various food procurement channels. Only a fairly narrow range of usual suspects has been the subject of study, however, including conventional grocery stores and community supported agriculture. This article considers the same question about community food projects; specifically, it explores the nature of customers’ involvement in, and perceived benefits from, a Good Food Box (GFB) programme in south-eastern Ontario, Canada. Using qualitative evidence from mail-in surveys and interviews, the paper draws from Foucault’s later work to consider the construction and maintenance of particular socio-spatial relations of care for both self and proximate others through food provisioning. As a predominantly self-caring act, GFB participation is motivated by frugality and physical health. When participants care for others through their patronage, prominent themes include helping less economically fortunate others, local farmers and family. The paper concludes by emphasizing the pervasiveness of care in consumerist activity and with outstanding questions about caring at a distance and the politics of educating consumer-subjects for ethical consciousness-raising.
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.
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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.026 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".