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Record W3191634878 · doi:10.1108/jkm-10-2020-0774

Individual knowledge measurement: organizational knowledge measured at the individual level

2021· article· en· W3191634878 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 · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsLakehead University
Fundersnot available
KeywordsTacit knowledgeRespondentKnowledge managementInvestment (military)Body of knowledgeKnowledge sharingOrganizational learningKnowledge value chainOriginalityProduction (economics)BusinessPsychologyComputer scienceSocial psychologyCreativityEconomicsMicroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Purpose Fundamental classifications of knowledge may be measurable as factors of production and can reveal evidence of specialization between adjacent stages of production even in the presence of shared substantive knowledge. This study of aims to distinguish between, and empirically measure, relative reliance on fundamental classifications of knowledge at the individual level. Design/methodology/approach In this study, investment managers were asked in an online survey to weigh their relative reliance on tacit, codified and encapsulated knowledge in executing different investment strategies for diverse client groups. Measures of relative reliance on each fundamental classification of knowledge were derived from weights assigned by each survey respondent in a series of six questions. Findings Survey respondents provided reliable measures of their relative reliance on tacit, codified and encapsulated knowledge. Reliance on these fundamental classifications of knowledge is shown to differ between investment managers, depending on the investment strategies being used and client groups served. These differences were exhibited notwithstanding all the respondents sharing common substantive knowledge. Research limitations/implications Measures of relative reliance on three classifications of knowledge were based on self-reported ratings rather than on objectively observed phenomena, making them subject to measurement error. Therefore, researchers are encouraged to observe relative reliance on tacit, codified and encapsulated knowledge in future studies. Originality/value The divergences in relative reliance on the fundamentally different knowledge-based factors of production were found in the presence of jointly held substantive knowledge, suggesting that fundamental classifications of knowledge are measurable and can provide evidence of specialization.

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)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.088
GPT teacher head0.250
Teacher spread0.162 · 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