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Record W2955994317 · doi:10.29173/mocs133

Strategies for Building Information Modelling Adoption in the South African Construction Industry

2019· article· en· W2955994317 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaProcurementBuilding information modelingBusinessWork (physics)Construction industryQuestionnaireProcess managementTest (biology)Process (computing)Knowledge managementMarketingOperations managementEngineeringConstruction engineeringComputer science

Abstract

fetched live from OpenAlex

The present state of the construction industry worldwide requires continual improvement. The quest for improvement is to the advantage of all concerned stakeholders. Innovation has been identified as this improvement measure. Building Information Model (BIM) is an example of such innovation in the construction industry. This work presents the strategies required for full adoption of BIM among construction professionals in South Africa. The study conducted a questionnaire survey among construction professionals in Gauteng province, South Africa. Data gathered were analyzed using percentage, mean item score and Kruskal-Wallis H-Test. The reliability of the questionnaire was also determined using Cronbach-alpha test. Embracing BIM requirements in construction supply chain, encouraging stakeholders collaboration, clear understanding of procurement process, and interpretation of accurate information are identified as key strategies for proper BIM adoption in for construction activities in South Africa

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.944

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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