Factors Affecting Knowledge Transfer in Public Organization Employees
Bibliographic record
Abstract
Managing knowledge is considered an essential resource for both public and private sector organizations. Effective transfer of knowledge (KT) among the employees could give a better platform in public entities to serve its clients in a more innovative and efficient way. In the context of Southeast Asia, studies on KT in public offices in Brunei compared to that in Singapore and Malaysia is relatively low. This study has made an attempt to investigation the relationship between cultural elements (trust, communication between employees, rewards and learning & development) and Knowledge Transfer with organizational socialization as a moderating variable. A structured questionnaire survey was conducted to collect responses from a range of public sector employees. In results the findings reveal that there is a significant relationship between learning & development and KT, but the hypotheses related to the other three variables: trust, communication and reward remain insignificant. On the other hand with the moderating effect trust shows significant influence over KT in building relationship with help of socialization.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".