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Record W4210755045 · doi:10.32920/19067645

Opportunities and barriers to sustainable urban development: an analysis of the Toronto Green Standard (Version 3)

2022· preprint· en· W4210755045 on OpenAlexaffabout
Ross Edwards

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsMcMaster UniversityToronto Metropolitan University
Fundersnot available
KeywordsIncentiveSustainabilitySustainable developmentContext (archaeology)BusinessEnvironmental economicsNormativeUrban planningEnvironmental planningRegional scienceEconomicsEngineeringPolitical scienceGeographyCivil engineeringMicroeconomics

Abstract

fetched live from OpenAlex

<div>The City of Toronto has pushed for sustainable development as a normative goal through the creation of the ‘Toronto Green Standard’ (TGS). The TGS requires all developments in the municipal boundary to meet a specified level of sustainability requirements. Since 2018, the TGS has provided the opportunity to reach three voluntary tiers beyond the required tier (tiers 2-4), further enhancing sustainable building performance in exchange for a development charge</div><div>refund. This report aims to determine the development characteristics most associated with Tier 2+. Results indicate that Tier 2+ developments are typically large-scale and mixed-use but vary given geographic context and developer characteristics. Moreover, results suggest that the</div><div>development charge refund may not be a sufficient incentive for most developers, indicating a need for incentive reform. This research is a significant case study for planners considering the challenges and opportunities of encouraging sustainability in urban development.</div><div>Key Words: Sustainable Development, Resilience, Toronto Green Standard, Incentives</div>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 designSimulation or modeling
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
Published2022
Admission routes2
Has abstractyes

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