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Record W7101421026 · doi:10.21083/crrf.v27i1.8591

FarmWorks – providing community-based capital for farms and food

2025· article· W7101421026 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)Production (economics)Capital (architecture)Rural areaCapital investmentCapital marketRural communityFood processing

Abstract

fetched live from OpenAlex

Food production is fundamental to strong, rural communities and a key component of rural economic strength. Over the last half century, Atlantic Canada has witnessed a progressive erosion of food security, and an increased reliance on imported food. In December 2011, a small group of community leaders launched FarmWorks Investment Cooperative Ltd., a for-profit cooperative focused on providing strategic and responsible community investment in food production, processing, and distribution. Since 2011 FarmWorks has raised over $1 million in private investments under the umbrella of Nova Scotia’s Community Economic Development Investment Fund (CEDIF) program. FarmWorks is promoted to community members as an investment vehicle that keeps financial resources in the Region and supports the local agri-food economy, Investors benefit from significant tax rebates under CEDIF. In less than 4 years of operation, FarmWorks investments have had measurable success in supporting agri-food business start-ups and expansion, focusing on both market pull (restaurants, and processors featuring local products) and primary production (farms and food distributors). To date some 35 businesses have received FarmWorks loans, following rigorous review of business plans and financial viability. This presentation will describe the evolution of the cooperative and its impact on rural innovation and sustainability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.234
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it