Comparing education for sustainable development in initial teacher education across four countries
Bibliographic record
Abstract
Purpose The purpose of this paper is to undertake a cross-comparative inquiry into Education for Sustainable Development (ESD) related to governance, initiatives and practices in initial teacher education (ITE) across four countries with very different contexts – Sweden, Scotland, Canada and Australia. It provides insights into issues arising internationally, implications for ESD in ITE and offers learnings for other countries and contexts. Design/methodology/approach A cross-comparative study design with overarching themes and within-case descriptions was applied to consider, compare and contrast governance characteristics, initiatives and practices from each context. Findings The approaches to governance, initiatives and practices that each country adopts are unique yet similar, and all four countries have included ESD in ITE to some extent. Comparing and contrasting approaches has revealed learnings focussed on ESD in relation to governance and regulation, practices and leadership. Research limitations/implications Making comparisons between different contexts is difficult and uncertain and often misses the richness and nuances of the individual sites under study. However, it remains an important endeavour as the challenges of embedding ESD in ITE will be better understood and overcome if countries can learn from one another. Originality/value Scrutinising different approaches is valuable for broadening views about possibilities and understanding how policies and initiatives translate in practice.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".