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Record W2279445838 · doi:10.3963/jmpm.v3i3.159

A Framework for Knowledge Management in Project Management Offices

2016· article· en· W2279445838 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

VenueJournal of Modern Project Management · 2016
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsKnowledge managementPMOS logicProcess managementComputer scienceProject managementProject management triangleKnowledge value chainBusinessEngineering managementOrganizational learningEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Nowadays, knowledge management becomes a key challenge in modern organizations, especially project-based organizations. As a central unit in a project-based organization, a project management office (PMO) plays a pivotal role in projects’ success and organizational performance. Consequently, PMOs need to build an effective knowledge management system that renders them more efficiency and effectively. This paper aims at proposing a conceptual framework for promoting knowledge management in PMOs. The paper begins with a review of the literature on knowledge management and activities in PMOs to provide a clear understanding of knowledge management in PMOs. Then the paper suggests an overall architecture of the knowledge infrastructure for PMOs. Finally, a framework is proposed for building an effective knowledge management system for PMOs based on the perspective of knowledge components that could help PMOs create more business value by classifying information formally and enabling its transformation into valuable knowledge assets.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.586
Threshold uncertainty score0.749

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 communication0.0000.001
Open science0.0020.001
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 head0.039
GPT teacher head0.309
Teacher spread0.269 · 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