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Record W1564430712 · doi:10.15353/cfs-rcea.v2i1.29

Local food, farmland, and urban development: A case of land grabbing North American style

2015· article· en· W1564430712 on OpenAlexaffvenueabout
Elizabeth Smythe

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsConcordia University of Edmonton
Fundersnot available
KeywordsZoningSpeculationLand grabbingFood securityInvestment (military)Food processingBusinessLand useAgricultureEnvironmental planningGeographyPolitical sciencePoliticsEcology

Abstract

fetched live from OpenAlex

This article examines emerging forms of investment and land speculation and their implications for local food movements in urban areas. These investment involve purchases of large tracts of land in growing urban areas with a view to profiting from re-zoning and exiting the market well before development occurs. It uses a case study of the struggle in Edmonton, Alberta over a city food and agriculture strategy and the protection of prime food producing land in the northeast from urban development. The article shows how local food activists were able to mobilize citizens in support of local food and preservation of the land and were able to initiate a process of linking land use decisions to a food and agriculture strategy. However, the power of development interests and the planning process resulted in a strategy which was weak on preserving land for food and the adoption of a land development plan which preserves little land and threatens the future of existing food producers in the area. The article argues that new forms of land grabbing in North America pose challenges to movements seeking to preserve local food production.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.215
Teacher spread0.172 · 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

Citations4
Published2015
Admission routes3
Has abstractyes

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