What Makes a CSA a CSA?
Bibliographic record
Abstract
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.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.021 | 0.043 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 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".