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Record W2133015697 · doi:10.3390/su2010215

Community Vitality: The Role of Community-Level Resilience Adaptation and Innovation in Sustainable Development

2010· article· en· W2133015697 on OpenAlexafffundabout
Ann Dale, Chris Ling, Lenore Newman

Bibliographic record

VenueSustainability · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsVitalitySustainable developmentAdaptation (eye)Resilience (materials science)Psychological resilienceCornerstoneSustainable communityIntervention (counseling)Scale (ratio)Environmental planningSustainabilityCommunity resilienceCommunity developmentEconomic growthEnvironmental resource managementSociologyPolitical scienceGeographyPsychologyEngineeringEcologyEconomicsSocial psychology

Abstract

fetched live from OpenAlex

Community level action towards sustainable development has emerged as a key scale of intervention in the effort to address our many serious environmental issues. This is hindered by the large-scale destruction of both urban neighbourhoods and rural villages in the second half of the twentieth century. Communities, whether they are small or large, hubs of experimentation or loci of traditional techniques and methods, can be said to have a level of community vitality that acts as a site of resilience, adaptation and innovation in the face of environmental challenges. This paper outlines how community vitality acts as a cornerstone of sustainable development and suggests some courses for future research. A meta-case analysis of thirty-five Canadian communities reveals the characteristics of community vitality emerging from sustainable development experiments and its relationship to resilience, applied specifically to community development.

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)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0050.033
Scholarly communication0.0050.007
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.264
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations79
Published2010
Admission routes3
Has abstractyes

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