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Record W2517998969 · doi:10.1177/0739456x16664788

Integrated Community Sustainability Planning in Atlantic Canada: Green-Washing an Infrastructure Agenda

2016· article· en· W2517998969 on OpenAlexafffundabout
Jill L. Grant, Timothy Beed, Patricia M. Manuel

Bibliographic record

VenueJournal of Planning Education and Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Patient Safety Institute
KeywordsSustainabilityMandateGovernment (linguistics)PoliticsPopulationBusinessState (computer science)Population growthSustainability organizationsPublic administrationEnvironmental planningSocial sustainabilityEconomic growthEnvironmental resource managementPolitical scienceEconomicsGeographySociology

Abstract

fetched live from OpenAlex

In 2005 the Canadian federal government initiated a New Deal for Cities and Communities. The program, which involved bilateral agreements with provincial governments, promised substantial funding to municipalities to promote integrated community sustainability through capacity building and infrastructure renewal. We evaluate the content of sustainability plans and the processes that produced them in one region: Atlantic Canada. The findings suggest that although the state mandate and funding resources produced a large number of sustainability plans, changing national political priorities and local desperation for economic and population growth undermined the program’s initial commitment to and potential for environmental and social 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 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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0140.003
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.050
GPT teacher head0.400
Teacher spread0.351 · 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 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

Citations16
Published2016
Admission routes3
Has abstractyes

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