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Record W3042325496 · doi:10.15353/cfs-rcea.v7i1.390

What Makes a CSA a CSA?

2020· article· en· W3042325496 on OpenAlexaffvenueabout
Zhenzhong Si, Theresa Schumilas, Weiping Chen, Tony Fuller, Steffanie Scott

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsUniversity of GuelphWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsVariety (cybernetics)CollectivismChinaIdeologyShareholderIncentiveIndividualismPoliticsPublic economicsEconomicsBusinessSociologyPolitical scienceMarket economyFinanceCorporate governanceLaw

Abstract

fetched live from OpenAlex

In different parts of the world, community supported agriculture (CSA) has taken a variety of organizational forms, drawn on different ideologies, used a variety of land tenure arrangements, and taken on varied types of market relations in terms of how they arrange sales and memberships. Despite this, comparative studies of CSAs are sparse. Based on interviews and survey results, this paper develops a framework to compare CSAs in Canada—where this system has evolved for the last 30 years as an alternative to industrialized agriculture—with those in China, where CSAs have emerged since the late 2000s, mainly in response to food safety and health concerns. The comparison is based on their initiators’ motivations, economic characteristics, ecological practices, shareholder relations, and community building. We find that in both Canada and China CSAs are struggling to maintain the movement’s original values and be economically viable. They are moving away from the traditional ‘risk sharing’ approach underpinning the model and adopting more flexible payment mechanisms. However, other original tenets of the CSA model, such as member engagement, are strengthening. This poses a definitional challenge—what makes a CSA a CSA? We conclude that CSAs mix capitalist and other-than-capitalist economic logic, blend traditional, organic, and productivist ecological relations, and demonstrate both individualist and civic collectivist politics simultaneously. These characterizations are what make a CSA a CSA in contemporary Canada and China.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.056
GPT teacher head0.228
Teacher spread0.171 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2020
Admission routes3
Has abstractyes

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