Growth Trajectory and Support Needs of the Food Artisan Economy: Insights from Rural BC
Bibliographic record
Abstract
Food artisans play a critical role in rural diversification by turning local resources into consumable products using traditional practices. This paper describes a study of BC’s food artisan sector including: a definition and description of food artisans, growth in consumer demand and business, distribution mechanisms and markets, contributions to employment, future business plans and challenges to growth. The study found that consumer demand for products has been increasing whereby 80% of artisans indicated increased demand for their products over the past 3 years, Demand was generated from both resident markets (70%) and visitor markets (30%). Similarly, 85% of artisans indicated business growth over the past 3 years and 86% indicated that their future plans were continued growth. Businesses generated 100% of employment income for 48% of the artisans, with another 40% earning at least 50% of their income from their business. Employment generated by the artisan businesses was more likely to be full time and permanent, with little fluctuation in the averages by season. Artisans used a diverse distribution strategy with the top mechanisms being in local shops, farm markets, local grocery stores and restaurants. The top challenges impacting business growth were difficulties in distributing products, marketing, and accessing capital for expansion. The study provides those involved in economic development, food tourism, and business development new insights on the relative importance of the food artisan sector and its role in place making.
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 | 0.000 | 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 | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".