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Exploring the impacts of Canadian agrihoods as a form of development-supported agriculture

2022· article· en· W4408460362 on OpenAlexaffvenueabout
Martin Straathof

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAgricultureGeographyBusinessEnvironmental planningArchaeology

Abstract

fetched live from OpenAlex

The development of agrihoods is a growing trend in the real-estate and development market and yet little is known about their efficacy at providing the variety of benefits they are said to deliver. This presentation will provide an overview of commonly cited benefits of agrihoods, while reflecting on the perception that they are a form of development-supported agriculture. An overview of the project will break down key definitions used to conceptualize agrihoods as a mechanism to support the preservation of farmland and explore the gaps in knowledge that contribute to the dangers of assuming their beneficial impacts. The presentation will take you through the purpose of exploring Canadian agrihoods and their impacts on the agricultural system, surrounding communities and their residents. You will be guided through the anticipated research results that might infer how agrihoods can be used as a tool for developing healthier, happier, and more resilient communities. This study aims to provide policy makers, municipalities, planners and farmers valuable insight and knowledge needed for the likely increase in agrihood development proposals, considerations for edge-planning, and alternative opportunities for preserving farmland.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.638
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.269
Teacher spread0.214 · 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 teacher head, 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
Published2022
Admission routes3
Has abstractyes

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