Ecojustice in Pre-Service Teacher Education: A Thematic Literature Analysis
Bibliographic record
Abstract
Integrating ecojustice into pre-service teacher education is critical to addressing the interconnected challenges of environmental degradation and social inequality. This study examines the incorporation of ecojustice principles into teacher education programs, emphasizing their importance in preparing educators to engage students with sustainability and equity issues. Key findings reveal that while ecojustice is gaining theoretical recognition, its practical application remains limited. The research recommends the implementation of experiential learning, culturally responsive pedagogies, and Indigenous knowledge systems to enhance ecojustice education. Findings underscore the necessity of comprehensive frameworks that equip pre-service teachers with the theoretical and practical competencies required to promote sustainability and social responsibility. This research contributes to transforming teacher education to address 21st-century environmental and social challenges. Keywords: Literature Review, Ecojustice, Pre-service Teacher Education, Environment Education, Experiential Learning, Culturally Responsive Pedagogy, Indigenous Knowledge
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".