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Record W2971528707 · doi:10.1139/cjce-2018-0461

Metaphors of collaboration in construction

2019· article· en· W2971528707 on OpenAlexvenueno aff
Danilo Gomes, Patrícia Tzortzopoulos

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsConsistency (knowledge bases)Knowledge managementSociologyComputer scienceConceptual frameworkEngineering ethicsEpistemologyManagement scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

Collaboration is essential for the success of construction projects. However, the concept of collaboration is unclear, and the term is often related to different meanings. Construction research defines collaboration in different ways, having been influenced by other research fields (e.g., social sciences and philosophy). This paper discusses existing definitions of collaboration and how they relate to three perspectives on the nature of collaborative interactions, linked to organisational metaphors. The research was developed through a literature review, including the conceptual analysis of existing definitions of collaboration. The discussion proposes that metaphors not only describe collaboration ontologically, but also establish different appreciative systems by which individuals conceive and evaluate their collaborative performance. The aim of this discussion is to address the lack of consistency in defining collaboration in construction, embracing the coexistence of interpretations. This can help researchers and practitioners understand how to overcome misunderstandings and explore initiatives to improve collaboration.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.266
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; 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
Published2019
Admission routes1
Has abstractyes

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