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Record W2322806996 · doi:10.3846/16484142.2016.1156021

An Octopus and a circle at the basis of a framework for the evaluation of sustainable mobility

2016· article· en· W2322806996 on OpenAlexafffund
Louiselle Sioui, Catherine Morency, Hubert Verreault

Bibliographic record

VenueTransport · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsPolytechnique Montréal
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsConceptualizationSustainabilityoctopus (software)Sustainable developmentStandardizationRepresentation (politics)Transport engineeringComputer scienceOrder (exchange)Risk analysis (engineering)Management scienceProcess managementEngineeringBusinessArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

Worldwide, transportation authorities are keen to implement sustainable development measures and to move toward a more sustainable mobility for people and goods. However, this implementation entails a rise in the need for a sustainable development assessment framework for mobility, in order to compare different projects or to monitor a given area. This paper addresses the issue of conceptualization and standardization of the evaluation of sustainable development in transportation, by proposing a framework, which seeks to meet the various needs of transportation planners. This framework aims to provide an exhaustive view of the sustainability features (through its three main dimensions), as well as to clarify the concept of sustainability in transportation by embedding links between actions and impacts. This paper presents the basis of the framework developed as an interactive tool: (1) a representation named ‘Octopus’ categorizing the impact of mobility on the three dimensions of sustainable development and (2) a circular representation, named ‘Causal circle’, which integrates causal links between actions and impacts on these same dimensions.

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)0.011
metaresearch head score (Gemma)0.014
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0030.014
Scholarly communication0.0120.014
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.023
GPT teacher head0.319
Teacher spread0.296 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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