Narratives and the New Farmer in Cape Breton: <i>“It’s Who We Are”</i>
Bibliographic record
Abstract
Can small, diversified farms thrive, or even survive, in Canada’s current agricultural milieu? Can they stand against the highly industrialized operations encouraged by Canadian policy, international trade, and capital interests? This study suggests that there is reason for optimism. Well-known visionaries, Canadian and worldwide, note a “new trajectory” in the context of the looming failure of current systems in agriculture, based on concerns for the environment and on the relationship between producers and consumers. Approaches to small, diversified farming operations come under several headings: economical, post-productive, civic. But it is the concrete experiences of individuals, families, and communities that truly give weight to the potential for sustainable food production. This research on Cape Breton Island farming—where self-sufficiency in food production is a strong tradition—presents a range of farming “styles” (as defined by Jan Douwe van der Ploeg) that are related to land acquisition, innovative marketing, support services, decisions about farm size and products, and the benefits of non-farm work as a farm subsidy. Interview narratives give voice to the actions of Cape Breton Island farmers who work within an “isolation paradox” as a way forward for their small farms.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.037 | 0.031 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".