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Record W4312308582 · doi:10.4018/ijkm.313446

ICTs in Knowledge Sharing and Organization Culture

2022· article· en· W4312308582 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

VenueInternational Journal of Knowledge Management · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsLakehead UniversityUniversité Laval
Fundersnot available
KeywordsKnowledge managementKnowledge sharingInformation and Communications TechnologyInterpersonal communicationOrganizational cultureCompetitive advantageICTSBusinessKnowledge value chainValue (mathematics)Organizational learningComputer sciencePublic relationsPsychologyMarketingPolitical science

Abstract

fetched live from OpenAlex

This study analyzes the knowledge value chain of a center for continuing education that offers skill development programs for adult learners. It analyzes how the center can improve efficiency and capacity by effective knowledge sharing (KS) that requires both information and communication technologies (ICT) and the conducive organizational cultures. The case study methodology was used to study the factors that influence KS in an academic environment. KS depends on the type of knowledge, motivation, and opportunity to share. The results show that both knowledge management systems and a conducive organizational culture are needed to implement an effective KS strategy. Thus, the study focuses on the emergent approach, i.e., focusing on interpersonal dynamics and the nature of their daily tasks, and engineering or management approach, i.e., focusing on the infrastructure of KS. This study shows how systematic and organized KS can help an organization offer continuing education services effectively and improve performance in the competitive marketplace.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score0.460

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 communication0.0000.000
Open science0.0010.001
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 head0.020
GPT teacher head0.315
Teacher spread0.295 · 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