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Record W1997808463 · doi:10.1108/13673270210450432

A knowledge management reference model

2002· article· en· W1997808463 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 Knowledge Management · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCompetitive and Knowledge Intelligence
Canadian institutionsConcordia University
Fundersnot available
KeywordsKnowledge managementComputer scienceConstruct (python library)StructuringBlueprintConceptual modelReference modelProcess managementManagement scienceBusinessSoftware engineeringEngineering

Abstract

fetched live from OpenAlex

A three‐layer, cognitive domains, functional and resources, reference model for knowledge management systems is developed. This model aims at providing the basis for identifying the processes to be supported by any knowledge management support system (KMSS), for modeling the dynamics of these processes, for developing a framework of a business‐aware approach to KMSS development methodology, and for developing blueprints for information/communication technology (ICT)‐based KMSS. The first layer deals with the organizational knowledge and its characterization in terms of knowledge things. The concept of “K‐manipulating situation” is introduced and used as a conceptual construct for structuring the functional aspects of KMSS. While this construct combines knowledge and its manipulating processes, it also captures the social aspects of them by including the involved actors and their roles. Examples from Matsushita’s “Home Bakery” case study are used to illustrate the application of the reference model.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.007

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 head0.070
GPT teacher head0.272
Teacher spread0.202 · 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