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Record W7132870268

The Rouge Uncovered: Community Participation, Urban Agriculture and Power Dynamics in the Creation of Canada's first National Urban Park

2017· dissertation· W7132870268 on OpenAlexaboutno aff
Jina Gill

Bibliographic record

VenueTSpace · 2017
Typedissertation
Language
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsUrban agricultureSustainabilityAgricultureGovernment (linguistics)Environmental justiceUrban planningSpace (punctuation)National parkHegemonyInclusion (mineral)
DOInot available

Abstract

fetched live from OpenAlex

Local food production has been a defining goal of a healthy and resilient food system. In 2011 the Canadian government and Parks Canada committed to creating Canadaâ s first national urban park. The space in which land is used to undertake conservation efforts and develop sustainable farming is often associated with inequalities of larger society; whereby hegemonic practices of inclusion and exclusion are produced and/or reinforced. By employing an Environmental Justice framework this thesis investigates if and how small-scale farmers and community members have been included in the creation of the park, and how power, particularly in relation to the axis of difference, influences green space planning, local farming and sustainability in the Greater Toronto Area. Findings show extreme contention between farmers and environmentalists over productive parkland use and definitions of ecological integrity. This research also discloses the need for a more inclusive approach to community participation processes in green space planning and management.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.018
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.293
Teacher spread0.273 · 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
Published2017
Admission routes1
Has abstractyes

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