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Record W4237525101 · doi:10.22215/etd/2014-10288

Re-activating Farmland in Ottawa's Greenbelt: establishing a concept of infrastructure development in the southern farm sector

2014· dissertation· en· W4237525101 on OpenAlexafffundabout
Christine Legault

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsCarleton University
FundersAgriculture and Agri-Food Canada
KeywordsUrban sprawlEnvironmental planningGeographyAgricultureSustainabilityUrban planningExpropriationPopulationBusinessAgricultural economicsEnvironmental protectionCivil engineeringPolitical scienceEngineeringEcologyArchaeologyEconomicsSociology

Abstract

fetched live from OpenAlex

Established by the Greber Plan in 1950, the objective of Ottawa's Greenbelt was to create a federally owned green space that would contain the urban sprawl of the city.At the time of expropriation, the land mass that is now considered "the Greenbelt" was actively used for agriculture.Sixty-four years later, the population of Ottawa has outgrown its original boundaries and the Greenbelt has effectively become a transit corridor for the city's urban and suburban populations.The greenbelt is farmed less and less with each passing year and more questions arise as to its role within the city.This thesis explores the kinds of infrastructure that could be developed to reactivate Ottawa's Greenbelt.It includes a design proposal for the Southern Farm Sector that envisions a productive agricultural landscape focused on the production of locally grown food, public engagement and education, and sustainable development.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.331
Threshold uncertainty score0.666

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.014
Scholarly communication0.0080.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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 designQualitative
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
Published2014
Admission routes3
Has abstractyes

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