Carrying Stories From the Outside In: A Collaborative Narrative Into a Teacher Education Community
Bibliographic record
Abstract
As three professors working collaboratively in teacher education, we reflect on our participation as former graduate students in narrative research circles facilitated by Dr. Jean Clandinin (University of Alberta) and Dr. Michael Connelly (Ontario Institute for Studies in Education, University of Toronto). By drawing upon the stories that we carry from institutions outside Brock University, we inquire into how our narrative experiences inform our current positioning within a teacher education community. Situating our work within social constructionism and narrative inquiry honours our relational, co-constructed work. Reflecting on three central questions regarding our individual research circle experiences assists in understanding how our narratives overlap with our current community. We draw attention to unspoken tensions that are embedded while working in relation. We invite other scholars to consider how collaborative research circle experiences can be a powerful form of living in community and a means of enhancing scholarly writing and practice.Keywords: research circle; research writing; teacher education; narrative inquiry; social constructionism; self-study
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.033 | 0.037 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.004 | 0.008 |
| 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".