Global ranking of knowledge management and intellectual capital academic journals: 2017 update
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.
Bibliographic record
Abstract
Purpose The purpose of this study is to update a global ranking of 27 knowledge management and intellectual capital (KM/IC) academic journals. Design/methodology/approach The ranking was developed based on a combination of results from a survey of 482 active KM/IC researchers and journal citation impact indices. Findings The ranking list includes 27 currently active KM/IC journals. The A+ journals are the Journal of Knowledge Management and the Journal of Intellectual Capital . The A journals are the Learning Organization , Knowledge Management Research & Practice, Knowledge and Process Management , VINE: The Journal of Information and Knowledge Management Systems and International Journal of Knowledge Management . A majority of recently launched journals did not fare well in the ranking. Whereas a journal’s longevity is important, it is not the only factor affecting its ranking position. Expert survey and citation impact measures are relatively consistent, but expert survey ranking scores change faster. Practical implications KM/IC discipline stakeholders, including practitioners, editors, publishers, reviewers, researchers, students, administrators and librarians, may consult the developed ranking list for various purposes. Compared to 2008, more researchers indicated KM/IC as their primary area of concentration, which is a positive indicator of discipline development. Originality/value This is the most recent ranking list of KM/IC academic journals.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it