Classifying organizations by knowledge intensity – necessary next‐steps
Bibliographic record
Abstract
Purpose This study aims to empirically explore the key elements for classifying and differentiating knowledge‐intensive organizations (KIOs) from other traditional organizations. Design/methodology/approach The study's conceptual framework is based on the prevailing propositions from the literature on KIOs and is explored using a survey of knowledge management (KM) professionals, a purposely selected community of practice (CoP). Findings The results suggest that organizations can generally be divided into two groups – KIOs and non‐KIOs, and there appear to be some clear factors that differentiate KIOs from non‐KIOs according to the CoP. Research limitations/implications This study lays a foundation for the systematic development and evaluation of KIOs and their KM practices. The results from this study can stimulate issue formulation and hypothesis generation for investigation by KM researchers and academics. The study focused on a few types of organizations drawn from the literature which may limit the generalizability of the results. However, restricting the study to the core organizations identified in the literature provided the authors with leverage for an in‐depth empirical exploration of these organizations' characteristics. Practical implications To a KM practitioner this study aids in delineating the different elements to keep in mind when designing or evaluating KM practices in KIOs. Originality/value This paper is among the early works to empirically explore KIOs. It advances a framework of how to recognize the knowledge‐intense factors defining KIOs, thereby providing the required foundation for analyzing KM practices in KIOs. Also by identifying the core dimensions defining knowledge intensity, the study underscores the importance of the relations between workers, the community (organization) of which they are members, and the conceptions the workers have of their activities as presented in the theory of organizations as activity systems. While the importance of knowledge has often been demonstrated within work groups or for particular organizational processes, this study has demonstrated a useful foundation for analyzing an organization as a whole.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".