A Case Study of a Community of Practice among Pediatricians at BC Children’s Hospital, Vancouver, British Columbia
Bibliographic record
Abstract
Background: Medical advancement and complex healthcare practices require pediatricians to learn continually.However, they struggle with their Continuing Professional Development (CPD) due to a shortage of pediatricians, which leaves them with heavy workloads and insufficient time for CPD.The problem leads to poorer quality care and higher mortality rates in pediatric departments.Participating in Communities of Practice (CoP) at their workplaces seems to be beneficial for improving their CPD.Despite a body of literature supporting CoPs impact on pediatricians' practice, there is a lack of understanding about their nature, functions, and their role in improving pediatricians' CPD.Methods: This qualitative case study was conducted at BC Children's Hospital (BCCH) in Vancouver, Canada, to examine the BCCH CoP and its role in pediatricians' CPD.The study was guided by a community of practice learning framework, and four Research Questions (RQ) were discussed with nine pediatricians with different specialties about CoP participation and their CPD.The data collected from the semistructured interview was analyzed using ATLAS Ti to determine the main themes.Findings: This study demonstrated that participating in the community helped pediatricians keep up with current knowledge in their fields.They shared information and ideas with other members and colleagues.Together, they created tools, guidelines, websites, and educational materials.In conclusion, all participants agreed that joining the BCCH CoP benefited their ongoing professional development (CPD). Conclusion and Interpretation:Highlights of this research concluded that community membership positively impacts members' professional development.The majority of respondents indicated that the community enabled them to stay up to date on the latest developments in their fields.They also exchanged information and ideas with their colleagues.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".