Application of an Evaluation Framework for Extra-Organizational Communities of Practice: Assessment and Refinement
Bibliographic record
Abstract
Abstract: Communities of practice (CoPs) are groups of people who work together on an ongoing basis and share knowledge and expertise. CoPs exist both within and outside of organizations, although extra-organizational CoPs have received less evaluation attention. The primary objective of this study was to assess the applicability of a multi-level, multiple-value evaluation framework for extra-organizational CoPs. Qualitative interviews were conducted with an extra-organizational CoP—the Canadian Community of Practice in Ecosystems Approaches to Health (CoPEH-Canada). The evaluation framework oriented both the member interview guide and the deductive content analysis. The findings showed that the evaluation framework was sufficiently comprehensive to capture the values generated. Following reflection on these findings, challenges in its application and suggested revisions to the framework are provided; also discussed are limitations and strengths, evaluation research next steps, and the opportunities for future applications.
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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 | 0.018 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".