Bibliographic record
Abstract
Distancing in the food system prevents people from having full knowledge and making informed choices about what and how they produce, exchange, prepare, and eat food. This becomes problematic when the dominant industrial food system contributes to myriad negative human health, ecological, and social outcomes. This paper reports on findings from a study that aimed to better understand distancing from the perspectives of people engaged in resisting it, focusing on their motivations for action to inform policy approaches to improve food system health. The research, conducted in India and Canada, comprised participant observation with organizations working to connect the production and consumption of food, as well as interviews with activists, consumers, and farmers involved with those organizations. These food system actors were motivated primarily by a conviction that food is important, which was illustrated by meaningful relationships built and maintained through food, by soulful connections with food, and by a sense that everything – including food – is interconnected. The findings identify connection around food as a source of meaning in life. From meaning comes awareness of broader issues, a sense of value and care, and ultimately motivation for action or change. This could have implications for healthy food system governance if frameworks such as determinants of health and healthy food environments are used to inform healthy public policies that cultivate a sense of meaning and awareness of the intrinsic value embedded in food.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".