Challenges in Reorienting Early Childhood Education for Sustainability in Initial Teacher Education: Transforming, Creating and Expanding
Bibliographic record
Abstract
This editorial essay introduces a special issue on education for sustainability, early childhood education and initial teacher education. We adopt a duoethnographic approach to first provide an overview of the issues, gaps, tensions and challenges in past and current trends in early childhood education for sustainability (ECEfS) in initial teacher education (ITE). Then, from our perspectives as four teacher educators located in disparate regions of the world: Finland, Turkiye, Canada, and Australia, we invite readers into our own stories as a starting place to explore the papers within the special issue. Through this dynamic interplay of four critically questioning minds and five papers, we aim to transform, create, and expand understanding of the interplay between ECEfS and ITE. We acknowledge that readers will derive their own understandings and responses from the papers, hence, our interpretations are not prescriptive, but rather aim to provoke further contributions to an emerging and developing field. This editorial essay introduces a special issue on education for sustainability, early childhood education and initial teacher education. We adopt a duoethnographic approach to first provide an overview of the issues, gaps, tensions and challenges in past and current trends in early childhood education for sustainability (ECEfS) in initial teacher education (ITE). Then, from our perspectives as four teacher educators located in disparate regions of the world: Finland, Turkiye, Canada, and Australia, we invite readers into our own stories as a starting place to explore the papers within the special issue. Through this dynamic interplay of four critically questioning minds and five papers, we aim to transform, create, and expand understanding of the interplay between ECEfS and ITE. We acknowledge that readers will derive their own understandings and responses from the papers, hence, our interpretations are not prescriptive, but rather aim to provoke further contributions to an emerging and developing field.
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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 | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.030 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".