MétaCan
Menu
Back to cohort
Record W1978538169 · doi:10.1108/13673271311315141

Three shapes of organisational knowledge

2013· article· en· W1978538169 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 · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsLakehead University
Fundersnot available
KeywordsTacit knowledgeKnowledge managementTypologyKnowledge value chainExplicit knowledgeOriginalityProduction (economics)Value (mathematics)Computer scienceDomain knowledgeOrganizational learningBody of knowledgeSociologyQualitative researchEconomics

Abstract

fetched live from OpenAlex

Purpose This research seeks to respond to Simon's challenge to apply “an economic calculus to knowledge”. The paper aims to develop a typology of knowledge that may be fruitful in facilitating research in a knowledge‐based view of production. Design/methodology/approach The paper reviews the enduring literature on the knowledge‐based view of the firm (KBV) and gleans three classifications of organisational knowledge as distinct factors of production: tacit, codified, and encapsulated knowledge. Findings Differences between the tacit, codified, and encapsulated shapes of knowledge carry strategic implications for the firm along six important dimensions. Distinguishing between its three classifications sets the stage for measurement of knowledge as a factor of production. Research limitations/implications Distinctions between the three shapes of knowledge may be less defined in practice than in theory. The classification in which a repository of knowledge falls is dependent on the tacit knowledge being applied by the user. Software may be encapsulated to a user, but codified to its creator. Practical implications Recognition of the differences between the three shapes of organisational knowledge may help managers to: determine the most economic combination of knowledge to use in production; transfer knowledge more effectively within and across organisational boundaries; determine the most economic location of firm boundaries; and ensure value is appropriated for the firm. Originality/value The paper suggests that distinguishing and accentuating encapsulated knowledge as a distinct classification of knowledge can help advance the development of a strategic knowledge‐based theory of production.

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: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.003

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 head0.022
GPT teacher head0.237
Teacher spread0.216 · 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