Is Trust the Most Important Human Factor Influencing Knowledge Sharing in Organisations?
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
The present study explores several of the most significant social and cognitive human factors that have been found to motivate or inhibit organisational knowledge sharing in previous empirical studies. Of specific interest is the individual and collective effect that trust, shared language, shared vision, tie strength, homophily and relationship length have on three important conditions necessary for effective knowledge sharing to take place (i.e. willingness to share, willingness to use and perceived receipt of useful knowledge). The study also considers the nature of the employee working relationship (positive versus negative) and the form of knowledge sharing (explicit versus tacit). In total, 275 surveys were completed by employees working on projects at one of Canada's largest multijurisdictional law firms. Quantitative methods were used to examine the relationships between the dependent variables and independent variables, while controlling for all the other variables in the model.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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