Trauma‐Informed Climate Education in Couple and Family Therapy Training and Supervision
Bibliographic record
Abstract
ABSTRACT Climate change and environmental justice impact mental health directly and indirectly through exposure to traumatic events and subsequent traumatic stress symptoms. This is especially relevant for marginalised groups, who are disproportionately impacted by climate change and are more vulnerable to traumatic stress. We propose integrating discussion of the impact of climate change via systemic trauma education in couple and family therapy (CFT) training. The authors are based in the United States and Canada and specifically address programmes in this continent. However, readers elsewhere may still find our paper relevant. Exploring the connections between climate change, environmental justice and trauma, we identify moments for ‘when’ to teach about climate change and mental health in CFT training. Next, building on research from clinical fields, we propose utilising a trauma‐informed pedagogy for ‘how’ to have these discussions with care for trainee mental health. We propose embedding discussion about climate change within trauma education in CFT training so that future generations of systemic practitioners can grasp the relevance of climate in their clinical practice early in their development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".