Challenging Our Stories as Teacher Educators for Social Justice: Narrative as Professional Development
Bibliographic record
Abstract
In this paper we report on a collaborative self-study in which we reflect upon our practice as teacher educators through a critical multicultural and white studies framework. We developed a pedagogical tool for our own professional development as teacher educators, modeled on the type of narrative assignments we ask of our students. We wrote stories about difficult moments in our practice, shared these with colleagues and reflected upon their responses. In this activity, we aimed to practice what we preach, as we model our commitment to being life-long learners; our respect for the power of listening to others and considering multiple perspectives; and our constant desire to critique and transform our practice in ways that are more effective and contribute to the educational success of all students. Our analysis of our experience demands that we reconsider our assumptions about student learning, how we hold our students accountable, and how we are socialized as white women within the academy of higher education.Keywords: narrative; teacher education; multicultural education
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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 | 0.025 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.059 |
| Scholarly communication | 0.025 | 0.018 |
| Open science | 0.003 | 0.019 |
| 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".