Knowledge Management as Support for Innovation of Public Projects
Bibliographic record
Abstract
Knowledge is an important organizational asset and it is essential to ensure efficient performance and competitiveness. Knowledge Management (KM) appears, therefore, as an important tool to guarantee the identification, absorption, creation, sharing and application of organizational knowledge. Innovation is seen as the creation or improvement of methods, practices, technology, product or service. In this scenario, this research had as a general objective to carry out a study of the conceptual foundations of Knowledge Management which are valid for innovation in public projects and as specific objectives to carry out a theoretical-conceptual survey on Knowledge Management, characterize the relationship between Knowledge Management and innovation and point out the valid indications in this study that support the innovation of public projects. The question to be answered was: How can Knowledge Management be used to support innovation in public projects? This research was elaborated through the Content Analysis Method and presented, as a result, the conclusion that the KM process as a whole has practices that aim to create in an organizational environment conducive to the emergence of innovative thinking encouraging the sharing of knowledge and experiences, the search for solutions and making individuals better qualified.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".