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Record W7115713873 · doi:10.1016/j.esg.2025.100307

How to enhance continuity of strategic sustainable development work in municipalities and regions – findings from Sweden and Finland

2025· article· en· W7115713873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth System Governance · 2025
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsAcadia University
Fundersnot available
KeywordsSustainabilityWork (physics)Sustainable developmentAction (physics)Relation (database)Set (abstract data type)Strategic planning

Abstract

fetched live from OpenAlex

Despite numerous initiatives, methodologies and approaches, municipalities and regions continue to face challenges in sustaining long-term efforts toward sustainability. While continuously learning from mistakes and success factors, comprehensive recommendations for how to take a long-term approach for the work, specifically developed for leadership in local and regional contexts, are largely lacking. Therefore, the purpose of this study was to identify a comprehensive set of essential factors that could support long-term sustainability efforts. The study is mainly related to the Framework for Strategic Sustainable Development, but the findings are likely relevant also in relation to other comprehensive sustainability methodologies and approaches. Re-analysis of longitudinal data from action research in Sweden and Finland is supplemented by new qualitative data collection, the study identifies eight conditions for continuity. Being introduced to these conditions upfront may save valuable time and could be utilized as a checklist to be revisited regularly and to strive toward.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.596
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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