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Record W2054850642 · doi:10.3390/su6095512

Sustainability Assessment and Indicators: Tools in a Decision-Making Strategy for Sustainable Development

2014· article· en· W2054850642 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

VenueSustainability · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsDalhousie University
FundersVlaamse Interuniversitaire RaadBelgisch Ontwikkelingsagentschap
KeywordsSustainabilityStructuringSustainable developmentSustainability organizationsContext (archaeology)Sustainability scienceProcess managementManagement scienceSocial sustainabilityBusinessEnvironmental resource managementEngineeringPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Recognizing the urgent need for sustainability, we argue that to move beyond the rhetoric and to actually realize sustainable development, it must be considered as a decision-making strategy. We demonstrate that sustainability assessment and sustainability indicators can be powerful decision-supporting tools that foster sustainable development by addressing three sustainability decision-making challenges: interpretation, information-structuring, and influence. Particularly, since the 1990s many substantial and often promising sustainability assessment and sustainability indicators efforts are made. However, better practices and a broader shared understanding are still required. We aim to contribute to that objective by adopting a theoretical perspective that frames SA and SI in the context of sustainable development as a decision-making strategy and that introduces both fields along several essential aspects in a structured and comparable manner.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.012
GPT teacher head0.335
Teacher spread0.323 · 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