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Record W6926350367 · doi:10.25316/ir-17847

Potential residential spaces for local food production in a suburban municipality

2022· other· en· W6926350367 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicRace, Identity, and Education in Brazil
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityProductivityFood processingProduction (economics)YardCity region

Abstract

fetched live from OpenAlex

This case study aimed to examine the potential areas for local food production in the City of Langford, a suburban municipality on southern Vancouver Island, Canada. To this end, initially, different zones of Langford were inspected to identify the areas with potential for growing food. After the selection of the city center, neighbourhood, and hillside/shoreline as three city zones to be used as research cases, the data related to their various spaces, including roofs, balconies, and yards (back or front yards), were collected using field observations and aerial images. The obtained data were then utilized to estimate the area of the places with potential for local food growing. The results demonstrated that the total usable private open spaces in the City of Langford for local food production represents an area between 1.125 km2 and 2.25 km2 in various productivity scenarios. Based on the research findings, around 35% of residential open spaces might provide some areas for local food production in this city. This research also discusses the importance of urban gardening for global economic and social sustainability issues and offered some initiatives to encourage communities to take advantage of the current possibilities for 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.345
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.000

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 head0.027
GPT teacher head0.331
Teacher spread0.304 · 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
GenreOther

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 routes1
Has abstractyes

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