Developments in Practice IX:The Evolution of the KM Function
Bibliographic record
Abstract
In 2000, a group of knowledge managers from twenty-five companies met to discuss the current state of knowledge management (KM) in their organizations. KM was then in a very early stage of its existence and took a wide variety of forms. Most KM groups were experiencing difficulties determining an appropriate role and function for themselves. Organizations were undertaking many different activities under the banner of KM. These activities were often fairly wide-ranging in scope with broad, general goals. To better understand how KM had matured and to explore its likely future development, the authors convened a similar focus group of knowledge managers in 2003. We found that KM's objectives are now focused into more achievable goals. Increasingly, the emphasis is on delivering immediate, measurable benefits by leveraging knowledge that is already available in an organization rather than on creating new knowledge. KM also carved out some key responsibilities for itself, such as creating and maintaining both an Internet framework and a portal to internal company information, and content acquisition, synthesis, organization, and management. Overall, the KM function became considerably more practical in focus and much less academic. The biggest challenge facing KM in the future continues to be the need to demonstrate tangible, measurable value to the organization. Disillusionment with KM tools and an inability to find useful content are seen as key threats to KM's survival. Maintaining alignment with business objectives is thus the most important means of ensuring KM's relevance. The next few years will be crucial for KM. If it can make its mark and demonstrate its value, we can expect to see knowledge management grow and prosper. If it cannot, its growth could be stunted for many years to come.
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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 | 0.026 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.008 | 0.042 |
| Scholarly communication | 0.029 | 0.024 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".