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Record W2606434383 · doi:10.1080/14649365.2017.1315447

Socio-spatial relations of care in community food project patronage

2017· article· en· W2606434383 on OpenAlexaffabout
Melanie Bedore

Bibliographic record

VenueSocial & Cultural Geography · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsFrugalityPublic relationsConsumption (sociology)ProcurementSociologyIdentity (music)ProvisioningPoliticsMarketingPolitical scienceBusinessSocial scienceEngineeringAesthetics

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.253
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2017
Admission routes2
Has abstractyes

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