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Record W7033699149

Review of the project management practices from the contractors' perspective to respond to the identified critical challenges in the Canadian green construction industry

2023· other· en· W7033699149 on OpenAlexaffabout

Bibliographic record

VenueEspace École de technologie supérieure (École de technologie supérieure) · 2023
Typeother
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsIncentiveConstruction industryGovernment (linguistics)Variety (cybernetics)Order (exchange)Process (computing)Green building
DOInot available

Abstract

fetched live from OpenAlex

Green construction has been adopted by the Canadian construction industry as a result of the demand for sustainable building techniques. However, green projects must overcome various challenges in order to be successful. 
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\nThis study identifies and analyzes the challenges encountered by green building contractors in Canada, as well as the strategies employed to respond to these challenges. 
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\nTen contractors were interviewed in addition to a literature review and the Fuzzy analytic hierarchy process (AHP) method. The literature review revealed that there are 34 challenges that fall into six categories. The Fuzzy AHP analysis ranked these categories as follows: market trends, time-related, financial, construction process-related, government-related, and technology challenges. 
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\nThe interviews revealed that contractors employ a variety of strategies to overcome such challenges, such as keeping up with industry trends, increasing efficiency, conducting research and development, implementing effective project management, advocating for government incentives, and fostering collaboration among stakeholders. 
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\nThese findings highlight the need for continued research and advocacy to promote green building practices and green construction incentives in Canada.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0050.001
Research integrity0.0010.003
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 head0.076
GPT teacher head0.323
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2023
Admission routes2
Has abstractyes

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