"Why nobody told me and why it would have been impossible to do so until now" : an autoethnographic inquiry into teaching and learning towards social justice in early childhood teacher education
Bibliographic record
Abstract
In this paper, a personal narrative autoethnographic methodology is used to begin mapping a transformative learning journey towards teaching and learning for social justice in early childhood teacher education. In autoethnography, personal lived experience is the primary source of data. This inquiry explores two stories of personal transformative learning using a journey metaphor to structurally frame the inquiry. Through a process of writing as inquiry (Richardson, 2003) and emotional introspection (Ellis, 1991) and using a conceptual framework based on postmodern perspectives, this autoethnographic research paper reveals the steps toward critical consciousness (Freire, 2006) taken by the author/researcher-a student in early childhood teacher education-as she uses personal narratives of lived experience in early childhood teacher education as primary data to explore the implications of this transormative learning process to explore themes around teaching and learning towards social justice in early childhood teacher education programs.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".