Moving forward while remaining rooted: A case study of the Ebytown Food Co-operative in Waterloo, Ontario (perspectives and findings from a member turned researcher)
Bibliographic record
Abstract
Retail food co-operatives provide a unique opportunity for community psychologists to work with democratically-controlled organisations that purport to offer each member control over the food she or he consumes on a daily basis. In this case study of the Ebytown Food Co-operative in Waterloo, Ontario, I document the activities of the co-op as it functions on a practical level, based both on my experiences as a researcher and an active member of the co-op. My thesis process was guided by the belief that research should be useful to the people with whom one works, and therefore, I followed a participatory approach. I gathered data through participant observation, document scans, and the membership questionnaire that I developed based on direction from both the co-op’s Board of Directors and a committee of dedicated co-op members. Once I analysed the findings from the questionnaire, I presented them at a co-op potluck and its 2002 annual general meeting. My findings revealed that numerous internal forces such as power and knowledge, issues of voice, the rights and responsibilities of members, and communication are at work in the co-op. The interaction of these forces affects the level of participation and the sense of community within the co-op. I discuss the findings in terms of power relationships and knowledge within the co-op, as well as in relation to Ebytown’s organisational development. I compare Ebytown to the current context of retail food co-operatives in North America and then offer some recommendations for the future of Ebytown. Lastly, I put forward suggestions for future research with food co-operatives and personally reflect on my research experience.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.044 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 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".