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Record W2094264687 · doi:10.3763/ijas.2009.0465

Agriculture on the edge: strategies to abate urban encroachment onto agricultural lands by promoting viable human-scale agriculture as an integral element of urbanization

2010· article· en· W2094264687 on OpenAlexaffabout
Patrick M. Condon, Kent Mullinix, Arthur Fallick, Mike Harcourt

Bibliographic record

VenueInternational Journal of Agricultural Sustainability · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsBC Centre for Disease ControlKwantlen Polytechnic UniversityUniversity of British Columbia
Fundersnot available
KeywordsAgricultureUrban agricultureUrbanizationPopulationSustainabilityFood systemsFood sovereigntyFood securityScale (ratio)BusinessEconomic growthEconomicsSociologyGeography

Abstract

fetched live from OpenAlex

In the Greater Vancouver region (Canada) tensions exist where urbanization encroaches onto agricultural land. A recently issued white paper proffered ideas to stimulate discussion on land-use plans and public policies to encourage and enhance agriculture while accommodating a doubling of the region's population. It evoked a visceral response from local and regional politicians, planners and agrologists who saw it as an heretical attempt to undermine land conservation. Proponents saw innovative strategies to ameliorate entrenched antipathy between competing perspectives. The core arguments and corresponding critique, outlined in this paper, bring to light elements of a broader debate about the vitality and sustainability of agriculture in British Columbia, as elsewhere, centring on issues of food security (supply) and food sovereignty (control) within two competing agricultural paradigms: human-scale agri-food systems and conventional industrial agri-business. Municipal enabled agriculture (MEA) is advanced as a catalyst for the full integration of the agri-food system within the planning, design, function, economy and community of cities and vice versa. MEA can make significant contributions to local and regional economies and has the potential to alter the way communities are designed to reduce unsustainability, planned to incorporate resilience, and organized so that they flourish socially and culturally.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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 designBench or experimental
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

Citations56
Published2010
Admission routes2
Has abstractyes

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