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Record W6996739400

Suburban subsistence agriculture: an Investigation of a suburban agriculture on the peripheral edge in the Greater Toronto Area

2020· dissertation· en· W6996739400 on OpenAlexaboutno aff

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2020
Typedissertation
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsSubsistence agricultureAgricultureExpropriationSustainabilityUrban planningSustainable developmentNatural resourceUrban agriculture
DOInot available

Abstract

fetched live from OpenAlex

The geographical expansion of large populated urban centres raises many environmental preoccupations, among which, the fact that it severely affects the way cities can rely on locally produced food. Suburban development makes cities grow outward from city centres, creating an expanding edge condition. Considered as a global phenomenon, the process of urban sprawl and expropriation generally take over prime agricultural land, thus making it difficult to implement environmentally sustainable conditions for large cities, particularly in regard to food production. Conceiving that agriculture and suburban areas can coexist with one another, this thesis investigates how architecture can contribute to the creation of subsistence agricultural conditions for food production within a suburban context. The suburban edge condition of Toronto, Ontario, offers a great terrain of investigation, and more specifically the town of Brooklin, where a suburban wall seems to move through the land, engulfing productive farms. If we learn how to design for this edge condition, we will, in consequence, develop solutions to the problem of urban growth and the loss of agricultural land. As the increasing demand for land impacts on the natural landscapes, farmland, and its people, a sustainable form of urban development should be considered. First, awareness needs to be raised about the unsustainable rates that agricultural lands are being consumed due to the expansion of cities. When cities take over the lands that fuel and feed them, the consequences are deeply problematic, both to city centres and suburban areas. For this reason, it is urgent to investigate how architecture can contribute to the introduction of subsistence agriculture for food production within larger suburban centres. In order to tackle this complex issue, different scales were addressed, ranging from the region to the scale of an object, trying to develop for each scale a strategy to connect experimental practices of agriculture to the site, its infrastructure and buildings. To create autonomous conditions, suburban farming and permaculture can be part of the urban infrastructure, which will have the potential to stimulate local food production at the domestic, neighbourhood, and city scales. The design of a new suburban edge will introduce a hub dedicated to food production, while relevant forms of housing were investigated as essential components for the suburban development model. Through the connection of these scales, this project probes how the edges of the Greater Toronto Area can become a model for a sustainable suburban subsistence agricultural community.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.212
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

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