Permanent small groups: Group dynamics, learning, and change
Bibliographic record
Abstract
INTRODUCTION: The concept of "communities of practice," a special facet of social constructivist learning theory, provides a new template against which we can examine the learning that goes on within permanent small groups of physicians. We interviewed participants and facilitators about the dynamics of these groups, their learning in conjunction with these groups, and the role the facilitator played to see the extent to which they captured the essence of communities of practice. METHODS: Semistructured interviews were conducted with physicians known to be participants or facilitators of small groups that met regularly. A constant comparative method was used for data gathering and analysis leading to coded themes, categories, and subcategories. The coding schemas were tested, the analyses were reviewed, and data were recoded as necessary. To ensure accuracy, interviewees were provided with a preliminary copy of the manuscript to ensure that the interpretation of the data was appropriately handled. RESULTS: Interviews were conducted with 10 facilitators and 22 group members representing 24 different groups of physicians. The groups appeared to function as communities of practice in which the members were supportive of each other's learning and respectful of one another, reporting little conflict. Members preferred to agree to disagree rather than pursue a "right" answer or consensus. Most of the discussion focused on scientific information and the way in which their colleagues approached common problems. Practice refinement rather than new directions in patient care appeared to be the goal. The facilitators in these groups played a key role in providing administrative support for the group and often the energy needed to sustain them. DISCUSSION: Small groups that meet regularly provide a supportive network to share knowledge and validate clinical experience. There is some evidence that the groups have the potential to become communities of practice but do not actually achieve that level of sharing. Research needs to be done to determine how these groups could become more powerful as communities of practice and vehicles for more substantive learning and change.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".