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Record W3216487771 · doi:10.32920/ryerson.14643927.v1

How can the development permit system be used to achieve residential intensification outcomes in the suburbs?

2021· preprint· en· W3216487771 on OpenAlexaffabout
Kelly A. Graham

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsToronto Metropolitan UniversityMcGill University
Fundersnot available
KeywordsZoningRedevelopmentPlan (archaeology)Environmental planningLand useGovernment (linguistics)Port (circuit theory)Development planBusinessLocal governmentOrder (exchange)GeographyPublic administrationPolitical scienceEngineeringFinanceCivil engineering

Abstract

fetched live from OpenAlex

The Province of Ontario made the Development Permit System (DPS) available to all municipalities in 2006, with the hope that municipalities could use this new tool to achieve various policy objectives, including intensification. Under the Growth Plan, municipalities have been instructed by the Provincial government to identify areas for redevelopment in order to meet the 40 per cent intensification target. Many suburban municipalities have been challenged to meet this target, and have requested Provincial assistance, and/or new regulatory tools. The DPS is one tool that has seen little use. This Major Research Paper explores the viability of the DPS for achieving intensification objectives in Port Whitby. The four existing DPS by-laws are compared, and other alternatives to zoning from different jurisdictions are reviewed. Lessons learned are incorporated into a set of recommendations to inform the Town of Whitby’s approach to their upcoming Port Whitby zoning review. Key words: Land use planning, intensification, policy implementation, planning tools

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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.

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
Published2021
Admission routes2
Has abstractyes

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