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Migrating Mennonites: Understanding the Impacts of Anabaptist Farmers on Local Food in Northern Ontario

2017· article· en· W3011294390 on OpenAlexaffvenueabout
Sara Epp

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAnabaptistsAgricultureFood securityGeographyExpansiveAgricultural economicsBusinessPolitical scienceEconomics

Abstract

fetched live from OpenAlex

As the cost of farmland in southern Ontario continues to increase, many farmers are seeking alternate locations suitable for agriculture. Northern Ontario, with an abundance of productive, less expansive land, has proven to be an opportune location for many farmers. In particular, over the past fifteen years, a significant movement of Amish and Old Order Mennonite farmers to northern Ontario has occurred. These farmers have increased access to local food, broadened the productive spectrum of crops and improved food sovereignty for many communities. Their impact on local communities has been significant, as has their impact on the broader farm community. Utilizing traditional farming practices, the Anabaptist community has significantly broadened the productive potential of northern farms, producing fruits and vegetables previously not grown locally. The potential to expand agriculture in northern Ontario is apparent and food sovereignty and security may be improved with the growth of this industry. As the potential movement of more Anabaptist farmers to northern Ontario is likely, it is important to understand their motivations to farm in the north and the challenges they incurred during and after this move. As part of this, this presentation will identify the impacts of Anabaptist farmers on both the production and consumption of local food in northern Ontario. Additionally, challenges regarding the expansion of agriculture in the north for Anabaptist farmers will be identified and opportunities to apply these lessons to the overall agricultural industry will be provided.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.270
Teacher spread0.226 · 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 designQualitative
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
Published2017
Admission routes3
Has abstractyes

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