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Record W970775266

The Role of Identity in Adopting Building Information Modeling: A Comparative Study

2015· article· en· W970775266 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.

Bibliographic record

VenueAmericas Conference on Information Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Montréal
Fundersnot available
KeywordsBuilding information modelingIdentity (music)Resistance (ecology)Construction industryKnowledge managementBusinessWork (physics)MarketingComputer scienceEngineeringOperations managementConstruction engineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

BIM is a modeling technology that allows architects and builders to visually create, analyze, and share building models. BIM is gaining a growing importance which may be reflected in the increasing number of owners who demand BIM use. However, despite the perceived uptick in demand for BIM, an industry wide adoption has not yet been reached. Likewise, the adoption of BIM enhanced business practices within both design and construction has been limited. While there are multiple barriers to BIM use, resistance to change has been identified by scholars as a major restraining force. Indeed, BIM prompts for substantial changes in the ways architects and constructors think and work which may question their performance and challenge their identities as competent workers. In this research, we address these dynamics, we use identity theory to gain an understanding on how identity accounts for acts of resistance and adoption of BIM in AEC industry.

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: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.355

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 communication0.0000.003
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 head0.050
GPT teacher head0.296
Teacher spread0.245 · 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