The impact of structuring characteristics on the launching of virtual communities of practice
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
Purpose Despite the increasing popularity of virtual communities of practice (VCoPs), our understanding of how to intentionally form, develop and sustain them is still at an embryonic stage. Aims to go some way to remedying this. Design/methodology/approach Investigates the attempt by 14 organizations to implement 18 VCoPs. Using existing documents, detailed logs, and focus groups, a large quantity of qualitative data was gathered, coded, and analyzed. Findings The study shows that the environment, the relevance of the VCoP's objectives to its members' daily work, and the degree to which the VCoP is embedded in the organizational structure of an organization are the three structuring characteristics most likely to explain the success or failure of a VCoP at the launching stage. Research limitations/implications The focus is limited to the launching phase; further research should investigate different stages of development. Practical implications The results may offer an indication as to the most important characteristics to consider at the launching stage of a VCoP. Management may want to work at changing the characteristics or take actions to counteract their obstructive effects. Originality/value This paper highlights the need for a contingency approach in VCoPs research and practice, and rids one of the misconception, which is pervasive in the extant literature, that all VCoPs are the same and should be managed the same way.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it