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Record W2240814112

Exploring the utilization of sustainable development strategies for the new parks in the municipalities of the Greater Toronto Area

2011· dissertation· en· W2240814112 on OpenAlexaboutno aff
Amir Ardeshir Nikzad

Bibliographic record

VenueThe Atrium (University of Guelph) · 2011
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentEnvironmental planningBusinessRegional scienceEnvironmental resource managementGeographyPolitical scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

Sustainable urban parks provide social and economical benefits to the residents and contribute to the urban ecosystem health. Municipalities are responsible for development and management of urban parks and the goal of this study was to better understand if, and why, the municipalities in the Greater Toronto Area (GTA) have utilized sustainable development strategies in the planning, design, construction and management for their new park projects. A qualitative study utilizing an in-depth interview format was created based on the principles of sustainable development compiled from the Sustainable Sites Initiative. A sample of four municipalities in the GTA was selected based on population and development growth and the park authorities were contacted. The results indicated few sustainable initiatives implemented in the design and management stages of park development. Understanding the constraints against these suggest that there may be potential to increase the sustainability of urban parks.

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)0.003
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 score0.171
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.222
Teacher spread0.143 · 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
Published2011
Admission routes1
Has abstractyes

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