Fostering a culture of inquiry through professional learning communities: one district's journey
Bibliographic record
Abstract
This case study of a school district change initiative, the implementation of professional learning communities (PLCs), is a narrative reflection from the perspective of a district leader in the role of Learning Communities Coordinator. The district's goal was to build teacher capacity to improve student achievement by establishing a PLC framework and a culture of inquiry to support teachers ' professional learning. Sources of data include the researcher's personal narrative with input from the district Superintendent and Director of Instruction. The author describes the steps, missteps, and leadership learning gained from the first two years of a five year initiative. Fullan 's (2007) stages of innovation and recommended components for district-wide reform as well as New understandings generated from this study may inform other school district leaders as they embark upon similar initiatives.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.014 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".