“I was purchasing it; it wasn't given to me”: Food project patronage and the geography of dignity work
Bibliographic record
Abstract
In response to food access challenges, local organisers are developing community food projects (CFPs) such as good food box programmes, mobile food vending, and non‐profit grocery stores, which (re)introduce affordable retail food options into under‐served communities. This paper explores the patronage of such retail‐based CFPs as dignity work. Whereas Jacobson (e.g., 2009a) elaborates a typology of social processes through which people undertake dignity promotion, this paper re‐examines such processes as personal politics of space. I argue that CFP patronage entails the strategic creation and destruction of physical and symbolic space in order to bring oneself in proximity to, or distance oneself from, morally un/desirable qualities and ways of being. Empirical evidence supporting this interpretation is drawn from mixed methods data collected from patrons and organisers of a Good Food Box programme in south‐eastern Ontario, Canada. The paper concludes with recommendations for supporting food projects’ role in protecting, promoting, and restoring their patrons’ dignity. It also encourages researchers to engage further with geographical imaginaries to theorise the spatiality of dignity work, building on its relevance to boundary processes, feminist care ethics, and “in the meantime” politics.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.036 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".