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Record W3197819069 · doi:10.3390/su13179861

Towards a Framework for Promoting Communication during Project Definition

2021· article· en· W3197819069 on OpenAlexaff
Hafsa Chbaly, Daniel Forgues, Samia Ben Rajeb

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsKnowledge managementProcess managementComputer scienceProject managementSustainabilityValue (mathematics)Project planningProject management triangleBusinessEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Project definition refers to the first three stages of a project life cycle, namely planning, programming, and preliminary design during which client needs are identified and translated into design solutions. An ill-defined hospital project definition may lead to hospital-acquired infections or patient mortality. The traditional management practices have been proved to be inadequate since architects usually do not communicate with users, and thus do not have detailed knowledge about how services are performed in the building. There is the need for more knowledge about the subject to improve and thus promote client value generation. This study first reviews factors that impact the communication between architects and clients during project definition based on the literature. The study then offers a framework based on these factors to help managers assess and improve communication between professionals and clients. The validity of the framework will then be empirically validated and revised based on findings of a longitudinal mega-hospital case study. The main objective of the current investigation is to improve the project definition practices of complex projects, and the assumption is that an effective communication provides more value to end users, as well as better project performance in terms of environmental and social sustainability.

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)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.101
GPT teacher head0.415
Teacher spread0.314 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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