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Record W3036274031 · doi:10.1139/cjce-2020-0077

CSR maturity model for smart city assessment

2020· article· en· W3036274031 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsWSP (Canada)University of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaturity (psychological)Capability Maturity ModelSustainabilitySmart cityKey (lock)PopulationProcess managementComputer scienceEngineeringPolitical scienceSociologyInternet of ThingsComputer securityEcology

Abstract

fetched live from OpenAlex

Population and urban growth are challenging traditional approaches to solving city-related problems. To meet these challenges, the concept of smart city/community (SC) has been introduced as a strategic solution. This research seeks to identify the key smartness dimensions of a city, build a corresponding novel smartness concept, and develop a full assessment model. The contribution of this research includes identifying three key dimensions for SCs: connectivity (C), sustainability (S), and resiliency (R); and developing a corresponding maturity model (MM) for SC assessment referred to as CSR-MM. The model’s applicability is validated by examining its conformance to MM design principles, available in the literature, and practically demonstrated via a case study (Fredericton Public Transit, New Brunswick). The assessment outcomes were compared against an international SC assessment tool ( ISO37120 2018 ). Municipalities will benefit from this CSR-MM in identifying maturity gaps, setting prioritized goals, and focusing on continuously improving citizens’ well-being.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.579

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 head0.020
GPT teacher head0.201
Teacher spread0.180 · 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