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Record W2314625786 · doi:10.5304/jafscd.2014.051.006

A Framework for Site Assessment Guides for Urban Impacted Soils: A Vancouver Case Study

2014· article· en· W2314625786 on OpenAlexafffundabout
Melissa Iverson, Maja Kržić, A. A. Bomke

Bibliographic record

VenueJournal of Agriculture Food Systems and Community Development · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsUrban agricultureEnvironmental planningDistribution (mathematics)StakeholderGeographyAgriculturePromotion (chess)Land useEnvironmental resource managementEnvironmental protectionBusinessCivil engineeringPolitical scienceEngineeringEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Urban agricultural activities, such as community gardening and urban farming, are becoming popular in many North American cities, including Vancouver, British Columbia (BC). Currently, demand for urban agricultural land in Vancouver is mainly met by reclaiming brownfields (vacant and often neglected tracts of land) and land owned or managed by schools, religious institutions, hospitals, and private residents, into gardens and urban farms. Before urban sites can be reclaimed, they need to be assessed for suitability for food production; however, many cities, including Vancouver, do not have locally adapted site assessment guides (SAGs). This paper describes the development of a framework for a SAG for Vancouver soils. The framework consists of the following five phases: (1) initial selection of properties and assessment approaches; (2) stakeholder feedback and subsequent revision of the properties identified in Phase 1; (3) additional feedback, revision, and finalization of the SAG; (4) distribution of the guides; and (5) ongoing updates and support. As part of framework development, we identified relevant site characteristics (e.g., soil properties, aspect, slope, amount of sunshine) for Vancouver and developed a Vancouver soil map. Distribution and promotion of the SAG through local organizations and societies started in 2010, and ongoing efforts regarding these initiatives are underway. The SAG framework used in Vancouver may be useful to other cities that wish to empower their citizens to create spaces for urban agriculture safely and successfully.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.035
GPT teacher head0.274
Teacher spread0.240 · 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.

Study designNot applicable
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

Citations1
Published2014
Admission routes3
Has abstractyes

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