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Record W4306737246 · doi:10.3390/buildings12101725

Sources of Challenges for Sustainability in the Building Design—The Relationship between Designers and Clients

2022· article· en· W4306737246 on OpenAlexaff
Nathália de Paula, Lincoln K. Jyo, S. B. Melhado

Bibliographic record

VenueBuildings · 2022
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsSustainabilityScope (computer science)Process managementKnowledge managementBusinessSoftware deploymentService designParticipatory designSustainable designService providerEngineeringService (business)MarketingComputer scienceOperations management

Abstract

fetched live from OpenAlex

Sustainability demands have changed the building design nature increasing the diversity of requirements, activities, agents, and tools. The aim of this paper is to investigate the sources of challenges in the relationship between architectural and engineering (AE) design firms and clients for promoting sustainability in the building design. Additionally, this study investigated the building information modeling (BIM) deployment by the firms that supports sustainability. The research method adopted is qualitative and participatory, based on focus groups. Two groups were interviewed, eight AE design firms and six developers and/or construction companies, gathering the points of view of service providers and their clients. The identified sources of challenges around sustainability include lack of communication and imprecision of definition, requirements, and scope. Additionally, management issues include performance evaluation, traditional work relationships, tools, and processes that do not support collaboration needs. In addition, AE design firms’ organization affects the client relationship and design quality, including the consideration of sustainability issues in the design solutions. The sources are found in the AE design firm’s processes of strategy planning, business and marketing, design, people, and knowledge management.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.057
GPT teacher head0.292
Teacher spread0.235 · 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 designObservational
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

Citations10
Published2022
Admission routes1
Has abstractyes

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