Exploring the Intellectual Core and Impact of the Knowledge Management and Intellectual Capital Academic Discipline
Bibliographic record
Abstract
The purpose of this study is to explore the intellectual core of the knowledge management and intellectual capital (KM/IC) academic discipline by analyzing cited and citing sources of the exemplary articles published in Journal of Knowledge Management and Journal of Intellectual Capital. Based on the findings, it is concluded that the KM/IC discipline: 1) builds its knowledge only upon works published in English language; 2) successfully disseminates its knowledge in both English and non-English language works; 3) does not exhibit a problematic self-citation behavior; 4) uses books and practitioner journals in the development of KM/IC theory; 5) converts experiential knowledge into academic knowledge; 6) is not yet a reference discipline, but is progressing well towards becoming one; and 6) exerts a somewhat limited direct impact on practice. Recommendations for various discipline stakeholders are offered.
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.
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 | 0.009 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".