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Record W3197166715 · doi:10.5304/jafscd.2021.104.005

Food sovereignty and farmland protection in the Municipal County of Antigonish, Nova Scotia

2021· article· en· W3197166715 on OpenAlexafffundabout
Greg Cameron, David J. Connell

Bibliographic record

VenueJournal of Agriculture Food Systems and Community Development · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Northern British ColumbiaDalhousie University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNova scotiaLegislatureFood sovereigntySovereigntyCorporate governancePolitical sciencePublic administrationAgricultureState (computer science)GeographyEconomyBusinessEconomicsFood securityPoliticsLawArchaeologyFinance

Abstract

fetched live from OpenAlex

This case study of the Municipal County of Antigon­ish (MCA) in the Canadian province of Nova Scotia assessed the extent to which agricultural land use planning accommodates those societal interests seeking to embed food sovereignty at the municipal level. Data were collected through content analysis of legislative documents, key informant interviews, and a review of the grey literature. Results suggest that the relatively weak municipal planning system in place prioritizes private interests over the public interest in farmland protection. The resultant gaps in the legislative setup in the MCA further reveal that food sovereignty actors and/or ideas have little influence over municipal governance of farmland protection. Broader historical and contemporary trends in Nova Scotia and Canada at large suggest that farmland will continue to lose ground to forces intrinsic to the dominant policy paradigm of market liberalism. Concluding thoughts call for “bringing back the (Canadian) state” itself as central to constituting a new agricultural policy paradigm.

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)0.002
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 score0.422
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.216
Teacher spread0.178 · 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

Citations7
Published2021
Admission routes3
Has abstractyes

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