Constructing local food systems : land and livelihoods in the Bella Coola Valley
Bibliographic record
Abstract
In the 20th century, advocates of the dominant mode of agricultural production advanced the key question, ‘how do we feed the world’. Critics of this Productionist paradigm assert that the resulting scarcity of farmers translates into a reduction of essential land-based knowledge and skills, and that centrally controlled solutions are inadequate to address the complex agro- and socio-ecological challenges of the 21st century. Interdisciplinary scholars are now looking beyond a narrow focus on production, and using a broader systems perspective to study the regeneration of food systems in local contexts. This dissertation contributes a case study of the agricultural food systems in the Bella Coola Valley in British Columbia, framed by the question, ‘how do we feed ourselves’. The research approach was a combined historical analysis and university-community partnership. The university-community partnership achieved the following main objectives during fieldwork in the Bella Coola Valley: we identified the biophysical resources for sustainable agriculture, surveyed current local food production, and explored the potential for increasing participation in agricultural production. Three key lessons emerged from this dissertation for initiatives aiming to regenerate agricultural food systems. First, because agricultural food systems form over time in specific places, it is crucially important to understand the formative historical processes. These include the evolution of indigenous food systems, dispossession and resettlement of land through settler colonialism, adaptation of livelihoods due to outside economic forces, and development of transportation networks. Second, redefining and reframing agriculture are important in colonial and small-scale contexts in order to see the diversity of agricultural activities. For the Bella Coola Valley, these activities include mixed homegardens, potlatch potato gardens, mixed small orchards, vine and berry patches, greenhouse and hothouse production, and livestock tending. Third, regenerating agricultural food systems is a continual and dynamic process, requiring an ongoing engagement between local leaders and outsiders, and between local, indigenous, and scientific forms of knowledge.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".