Climate emotions in early childhood: a conceptual framework for research, intervention, and policy action
Bibliographic record
Abstract
This paper introduces a comprehensive conceptual framework for understanding and addressing climate emotions in early childhood research, policy and practice, while supporting children’s emotional well-being in the face of environmental change. Recognising the growing psychological impact of the climate crisis on young children, the framework posits that climate emotions are shaped by four interdependent domains: Neurodevelopmental/Emotional Regulation Capacities, Caregiver/Educator Co-regulation, Symbolic/Imaginative Mediation, and Sociocultural/Environmental Climate Narratives. The framework moves beyond fragmented and often pathologising concepts like ‘climate anxiety’ and ‘eco-anxiety’ by offering a holistic, developmentally-sensitive view of both adaptive and maladaptive emotional responses. It directly addresses the absence of an integrated, developmentally specific, and cross-system framework for children up to age eight, a gap in the existing climate emotion models. Finally, the framework is translated into actionable policy and intervention strategies for researchers, clinicians, educators, and policymakers, arguing that a systems-level approach is essential to cultivate resilience and promote healthy development in the face of the global climate crisis.
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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 | 0.017 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".