Community financing for sustainable food systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since 2011, FarmWorks Investment Co-operative Limited (FarmWorks) has been boosting Nova Scotia’s farm and food economy through small loans to local food businesses. The fund relies on community investments and relationship-based lending, markers of the provincial government’s Community Economic Development Investment Fund (CEDIF) program. FarmWorks was motivated by decreasing food production, dwindling agricultural employment and the resulting decline of rural communities across the province. These factors were compounded by systemic changes including the increased financialization of the agri-food sector. As a social economy organization, FarmWorks seeks to remedy the shortcomings of the dominant food system by prioritizing the social and ecological regeneration of local communities. It simultaneously works with existing market structures while challenging mainstream practices and developing an alternative model. Through a document review, our paper assesses the extent to which FarmWorks has been successful in its efforts “to increase the viability and sustainability of agriculture and the security of a healthy food supply.” Specifically, we examine economic outcomes (employment, revenue increase, business expansion) as well as social impact of FarmWorks loans. We situate our analysis in literature on social economy, financialization, and sustainable food systems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it