Bibliographic record
Abstract
The world changed. More than ever information gains a strategic role in professional contexts. Organizations are told that they will not survive in the modern era without a strategy for managing and leveraging value from information (extended to knowledge). This means that organizations must change the way information is managed, from a “housekeeping” style to a transversal mode, similar to how Human Resources, Finance, or Information Technology departments. This paper recommends some actions to make information/knowledge management an asset to be measured and with an impact on career development. It is a qualitative analysis resulting from an exploratory literature review and its comparison with working experience and observation in the last 15 years as an information manager. Via this combination, it was possible to approach a different type of intellectual capital investment, resulting in the proposal of creating an information/knowledge ladder strategy followed by a new performance evaluation indicator resulting from the information/knowledge management investments. The key conclusion shows that although information/knowledge management is a key asset for success, it’s necessary to reinforce research and implementation studies in strategies that measure the returns on information/knowledge investments. It’s also fundamental to the role of the academic side, extra engaging with organizations but also investing more in studies and creating new measurement techniques and indicators to be explored by future information professionals, particularly information managers.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.276 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".