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Record W4415586403 · doi:10.21083/crrf.v29i1.7654

Structural Barriers to The Expansion of Organic Agriculture inCanada

2025· article· W4415586403 on OpenAlexaffabout
John F. Devlin

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCertificationOrganic farmingOrganic productOrganic certificationAgricultureGeneral partnership

Abstract

fetched live from OpenAlex

The organic farming movement has been expanding for more than 50 years in North America. Systems of organic certification have a much shorter history. Organic regulation and certification in Canada was introduced federally in 2005 and became operational in 2009. To trade agricultural products under an organic label in Canada requires third party organic certification if the product crosses a provincial boundary. Organic certification is provided by a number of certification organizations. But organic certification has not been embraced by all members of the organic movement and there has been a proliferation of labels for agricultural products claiming some degree of environmental sensitivity including: natural, pesticide free, free range, pastured, grass-fed, and local. While the demand for these products has been growing only certified organic products are regulated by law. This paper examines the diffusion of organic certification in Canada. It identifies the rate of diffusion and examines the different factors – policy and regulations, competition, pressure from consumer and environmental groups, business and farming associations that are influencing the decision to undertake and maintain organic certification in the face of the increasing competition from non-regulated alternatives. This paper is part of a research project funded by Canada’s Social Sciences and Humanities Research Council under its Partnership Development Grant. An early version of the paper was presented in the panel entitled "Diffusion of environmental innovations among micro small and medium enterprises: learning across disciplines and across cultures".

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.007
GPT teacher head0.206
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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