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Record W2810809212 · doi:10.1177/875697280603700203

Searching for Knowledge in the Pmbok® Guide

2006· article· en· W2810809212 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

VenueProject Management Journal · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsProject managementTacit knowledgeKnowledge managementOPM3Project management triangleEngineeringProcess managementBusinessEngineering managementComputer scienceSystems engineering

Abstract

fetched live from OpenAlex

A promising new topic for researchers who focus on project management is the application of knowledge management concepts as a way to improve project success. In this paper, knowledge management theory is used as a lens to examine the Project Management Institute's A Guide to the Project Management Body of Knowledge (PMBOK® Guide), because this book is globally influential among project managers. Several different theoretical frameworks are used. Results show that the PMBOK® Guide has a strong bias toward explicit and declarative (i.e., “how”) knowledge, and pays less attention to tacit and causal (i.e., “why”) knowledge. Our recommendations outline how the existing structure of the PMBOK® Guide can be preserved while the content is enhanced using knowledge management concepts that have been shown to be influential in enhancing project success. This is an enhanced and expanded version of a paper presented at the PMI Research Conference 2004 in London, England.

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)0.011
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.134
GPT teacher head0.438
Teacher spread0.304 · 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