Manitoba Shared Farming: An Examination of the Contributions of Southern Manitoba Community Supported Agriculture Initiatives for Rural Communities
Bibliographic record
Abstract
Using southern Manitoba as a case study, this paper explores the contributions made to sustainable rural livelihoods by direct farm marketing models such as Community Shared Agriculture (CSA) and farmer’s markets. Although the majority of farmer’s market vendors operate using conventional practices, many small-scale organic producers sell their goods via CSA and/or Farmer’s markets. Direct farm marketing models often exist in the informal economy and subsequently their economic and social impacts, contributions to farm and household income, and impacts on the broader community remain unmeasured. Existing research on CSAs focuses on social and ideological aspects largely ignoring the economic realities. Through the use of case studies, surveys of vendors and consumers, and interviews with key informants and market coordinators, this paper will examine the challenges to Manitoba organic producers and conventional vendors marketing through CSA’s and farmers ’ markets. Preliminary reviews of these challenges reveal them to mirror those faced by rural communities. Challenges include ageing populations, transportation, labor availability and cost, economies of scale, length of the growing season, lack of supports and marketing channels, and low rates of return. Among small scale organic producers concerns regarding equity and distribution of their products rank highly as a barrier to the establishment of sustainable pricing. Alternative models and regulatory reforms (including certification) are needed to increase the viability of local consumption at a socially acceptable price. Who should internalize the true costs of sustainable food production? Can organics provide a viable option for sustainable rural livelihood strategies?
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".