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Record W2601943512 · doi:10.1504/ijsd.2017.10004176

Implementing integrated community sustainability planning: a comparative case study of three mid-sized municipalities in Ontario, Canada

2017· article· en· W2601943512 on OpenAlexaffabout
Brandon Williams, Graham Whitelaw, Patrícia Hill Collins, Morgan Alger

Bibliographic record

VenueInternational Journal of Sustainable Development · 2017
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsSustainabilityEnvironmental planningSeven Management and Planning ToolsStrengths and weaknessesBusinessPoliticsEnvironmental resource managementRegional planningIntegrated business planningUrban planningProcess managementPolitical scienceEconomicsGeographyEngineeringOperations managementCivil engineeringMarketing

Abstract

fetched live from OpenAlex

Around the world, municipal governments are engaging with sustainability in daily practices. One approach gaining momentum in Canada is integrated community sustainability (ICS) planning, which involves integration of all sustainability pillars into policies and plans for more coordinated, inclusive approaches to planning and management. Drawing from established elements of effective ICS planning, we examined the implementation strategies of three mid-sized Ontario municipalities that use contrasting ICS planning approaches. While the cities studied address most elements of our analytical framework, each offers unique strengths and weaknesses. Overall, ICS planning appears flexible and adaptive enabling tailored approaches to unique political and fiscal realities.

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)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.802

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0220.006
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0010.001
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 head0.172
GPT teacher head0.463
Teacher spread0.291 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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