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Record W2005304630 · doi:10.1504/ijmdm.2008.017195

Behaviour validity of a simulation model for sustainable development

2008· article· en· W2005304630 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

VenueInternational Journal of Management and Decision Making · 2008
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsYork University
Fundersnot available
KeywordsComputer scienceSustainable developmentSystem dynamicsProcess (computing)Management scienceRisk analysis (engineering)AppealEconomicsEcologyBusinessArtificial intelligence

Abstract

fetched live from OpenAlex

System dynamics simulation models are well suited for the analysis of problems related to sustainable development. This is due to their ability to take an integrative view of social, economic and environmental factors and link the observable patterns to microlevel structure and decision process. Despite their capabilities, the acceptance of system dynamics simulation models by the broader community of decision makers is limited. We argue that reluctance by the system dynamics modellers to expose their models to formal behaviour validity procedures is the main problem. This leads to an outline of formal behaviour validity procedures available but less explored in system dynamics modelling 'repertoire'. An illustration of the multiple tests and the Theil inequality statistics for behaviour validity of a system dynamics simulation model for sustainable energy policy development follows. Finally, various conclusions on the increased appeal for simulation models for sustainable development initiatives are also presented.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.223
GPT teacher head0.436
Teacher spread0.212 · 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