MétaCan
Menu
Back to cohort
Record W2189354070 · doi:10.7492/ijaec.2014.007

The Cultural Ecosystem of Megaprojects: The Interconnectedness of Organizational Elements and their Wider Institutional Contexts

2014· article· en· W2189354070 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Architecture Engineering and Construction · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsEcosystemSociologyEnvironmental resource managementEconomic geographyKnowledge managementPolitical scienceGeographyEcologyEconomicsComputer scienceBiology

Abstract

fetched live from OpenAlex

In the multi-layered structure of megaprojects, organizational cultures emerge within different temporary multi-organizational teams (TMOs) responsible for execution. The cultural ecosystem in megaproject is conceptually articulated at the levels of their institutional settings to increase sustainable delivery. TMOs as meso-level coalitions are complex systems comprised of diverse public-private organizations responsible for delivering individual projects within the programme. Understanding these social and structural milieus provides a new groundwork for conceptual development and theorization of megaproject culture formation. Mirrored through its dynamics, ecology and development, this paper unravels how cultural features are affected by environment, effected in development, and transformed during the megaproject life. Contributions are made by shifting discourse towards a dynamic understanding of causal diversity that shape culture within TMOs to improve transferable practice. This investigative strategy challenges extant normative viewpoints. Indicating the need to reconsider existing perceptions and to embed norms of reflexivity beyond the mainstream megaproject management thinking.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.010
GPT teacher head0.255
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

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 designOther design
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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Architecture Engineering and ConstructionSame topicConstruction Project Management and PerformanceFrench-language works237,207