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Record W2555629863 · doi:10.29173/mocs15

Implementing Sustainable Construction Principles and Practices by Key Stakeholders

2016· article· en· W2555629863 on OpenAlexvenueno aff
Nnamdi Maduka, David Greenwood, Allan Osborne, Chika Udeaja

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2016
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessChampionSustainable developmentContext (archaeology)Promotion (chess)Order (exchange)Government (linguistics)QuestionnaireConstruction industryResource (disambiguation)Process managementEnvironmental resource managementEnvironmental economicsMarketingEngineeringPolitical scienceComputer scienceEconomicsConstruction engineering

Abstract

fetched live from OpenAlex

The term äóÖsustainable constructionäó» is used to highlight the responsibility of the construction industry in attaining sustainable development (SD). With the increasing necessity for resource efficiency and climate change adaptation, there is a need for construction key stakeholders to implement sustainable principles and practices in construction projects. In the UK context, engaging in such action will facilitate the government target of 80% greenhouse gas reduction by 2050 and also be a potential source of competitive advantage in the future. The aim of this study is to examine how the industry values and promotes sustainable principles and practices in construction projects. A quantitative research method was adopted in order to reach a wider audience in the industry. An online questionnaire survey was used to collect data. The key finding from the survey is that the level of construction industry promotion of sustainable principles and practices is less than it should be. The outcome of the survey suggests that the industry needs to strategise on how to champion and promote the implementation of sustainable principles and practices at a greater level if the industry is to contribute to the global quest for SD.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.236
Teacher spread0.215 · 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.

Study designNot applicable
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

Citations4
Published2016
Admission routes1
Has abstractyes

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