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Record W4250020396 · doi:10.32920/ryerson.14652417.v1

Regional contributions to achieving sustainability : an examination using sustainability-focused policies in regional official plans

2021· preprint· en· W4250020396 on OpenAlexaff
Elisabeth Perlikowski

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSustainabilitySocial sustainabilityIntergenerational equitySustainability organizationsEquity (law)Order (exchange)BusinessEnvironmental planningEnvironmental resource managementPolitical scienceEconomicsGeography

Abstract

fetched live from OpenAlex

This research examines the policy content of the Regional Official Plans in order to provide insight whether the regions of York and Peel are moving towards achieving sustainability. The study’s exploratory qualitative and comparative analysis examines the Regions’ contributions using the planning policies outlined in the recently released Regional Official Plans. Findings suggest that the Regions have emphasized sustainability-focused policies and have laid a foundation in achieving environmental and economic elements of sustainability. The analysis shows a low occurrence of policies that integrate social equity and justice issues with the economic and environmental objectives, which reduces the prospect of achieving sustainability. The comparative analysis suggests a number of directives that further can decrease the move towards achieving sustainability, including voluntary policies and indicators that may mislead a community in its progress towards sustainability. The study found that the Region of Peel has a higher presence of factors that can weaken the chances of achieving sustainability.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.318
Teacher spread0.290 · 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
Published2021
Admission routes1
Has abstractyes

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