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Record W2905613523

Growing Ontario Responsibly: A Look At The Impact Of The Growth PlanFor The Greater Golden Horseshoe On Ontario's Economic Environment

2017· article· en· W2905613523 on OpenAlexaboutno aff
Kelly O'Hanlon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGrowth managementTypologyPlan (archaeology)Horseshoe (symbol)BusinessGovernment (linguistics)Diversity (politics)Environmental planningLand useNatural resource economicsGeographyEconomicsEngineeringPolitical scienceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

This Major Research Paper (MRP) will examine the consequences of the proposed Growth Plan for the Greater Golden Horseshoe (GGH) on the economic trends of southern Ontario. As a type of regulatory tool, the Growth Plan has inevitable market impacts that must be studied, understood, and mitigated when making policy decisions. Increasing evidence has pointed towards housing affordability, and supply of land and housing types, as two broad market impacts of regulatory tools that fall under the branch of ‘growth management’, ‘urban containment’, and ‘smart growth’. The subject of this MRP is the economic impact of the Growth Plan for the Greater Golden Horseshoe, imposed by the provincial government, and implemented on a municipal level. In 2015, the province initiated its first ten-year review of the 2006 Growth Plan for the GGH. The province released proposed amendments to the Growth Plan in the summer of 2016 following an analysis by a selected panel of experts and input from community consultations. It is anticipated that these proposed amendments will exasperate the widespread affordability issues of the GGH, create a more homogenous built form and building typology, and ignore the diversity of municipalities across the impacted area. A thorough analysis of these adverse effects will be provided along with recommendations on how the province can better balance the environmental, social, and economic goals of the Greater Golden Horseshoe.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.183
Threshold uncertainty score0.948

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.266
Teacher spread0.242 · 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
Published2017
Admission routes1
Has abstractyes

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