Policy's Role in Socioagricultural Transition: A Community Study in Tatamagouche, Nova Scotia
Bibliographic record
Abstract
In Atlantic Canada, as in rural areas around the world, many citizens are engaged in ways to adapt innovative local level solutions to the challenges posed by globalized industrial agriculture. To prevent the further unraveling of community fabric and to promote rural resilience, there is a shift in some Atlantic Canadian communities towards what Thomas Lyson terms civic agriculture (2004). Using civic agriculture as a conceptual framework, this in-depth community case study found there is a strong community of Tatamagouche farmers who tend to operate on a small, labour-intensive scale, and who value direct links with consumers. This paper investigates civic agriculture initiatives using the narrative of past socio-agricultural transition to understand present-day challenges and opportunities in realizing a locally organized system of food production and distribution. Specific policy recommendations based on this study's findings include: the integration of local mentorship and experiential learning into agricultural education; strategic planning by the province for domestic consumption increases through existing buy-local campaigns and consumer education programmes; a review of regulatory standards to accommodate small-scale and diversified family farms; and start-up aid for community-scale agricultural cooperatives. Additionally, this paper calls for a broader shift in the philosophies that shape current policy choices and recommends reframing the mandate of governmental departments like Health and Environment to address small-scale community-based agriculture, and advocating for the political recognition of the non-commodity benefits of agriculture. Keywords: civic agriculture, agricultural education, family farms, agricultural cooperatives
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".