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Record W3186102064 · doi:10.29173/mocs195

Modelling International Project Feasibility of Sustainable Construction Management: Case Study of Tele-Communication Towers

2015· article· en· W3186102064 on OpenAlexvenueno aff
Samad M. E. Sepasgozar, Gholam Reza Shiran, Khalegh Barati, Renard Siew

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2015
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityRelevance (law)Project managementSustainable developmentDeveloping countryPhase (matter)EngineeringProcess managementEnvironmental resource managementBusinessEnvironmental economicsManagement scienceEngineering managementSystems engineeringEconomicsPolitical scienceEconomic growth

Abstract

fetched live from OpenAlex

This paper presents a new conceptual model for feasibility study of projects incorporating sustainability criteria. Large construction projects have an important influence on the attainment of sustainable development indices. Some of these projects particularly in developing countries have not sufficiently considered sustainability issues even with the participation of international companies in these projects during the feasibility phase as well as other phases such as design and operation. Previous studies have not addressed the relevance of the project feasibility phase in terms of sustainability performance. This paper is a result of the initial stages of an on-going study to develop a rigorous model of construction feasibility with sustainability considerations. Two case studies of similar construction projects were selected from two developing countries. The model for project feasibility study proposed in this paper includes economic, social, and environmental performance criteria in addition to traditional project criteria. The paper suggests there is an urgent need for shifting from the traditional approach of project feasibility study to a new approach embracing sustainability principles.

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 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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.262
Teacher spread0.232 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2015
Admission routes1
Has abstractyes

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