How Shared Language and Shared Vision Motivate Effective Knowledge Sharing Behavior
Bibliographic record
Abstract
Effective knowledge sharing within project teams is of critical importance to knowledge- intensive organizations. Prior research studies indicate a positive association between shared cognitive perspective and effective knowledge sharing behavior among co-workers. Building on these studies and drawing from theoretical foundations found in the sociological and social- psychological literature on organizational trust and knowledge sharing, this study sought to test the effect of shared perspective (i.e. shared language and shared vision) on organizational knowledge sharing behavior. The data were provided by 275 'legal professionals' and paralegals who were all knowledge workers engaged in shared legal project work at one of Canada's largest multijurisdictional law firms. The nature of their work required a significant reliance on co-workers for both explicit and tacit knowledge. Multiple regression analysis, among other statistical techniques, was used to test the hypotheses and determine significant relationships. Overall, having a shared cognitive perspective had a positive effect on knowledge sharing behavior in the firm. Results showed a positive relationship between shared perspective and willingness to share knowledge; where higher amounts of shared language or shared vision led to higher willingness by the respondent to share with their co-worker, regardless of working relationship. Results also showed a positive relationship between shared vision and willingness to use knowledge. Surprisingly, no significant relationships were found between shared language and willingness to use knowledge in either group. Interestingly, the results also suggested that both shared language and shared vision led to a significantly higher perception that knowledge received from positive referent co-workers was useful. However, neither shared language nor shared vision had a significant effect with negative referents. This finding suggested a need to further explore the effect of working relationships in subsequent research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".