The creative arts therapies and the climate crisis: Toward a framework for intentional engagement
Bibliographic record
Abstract
In the face of the deepening climate emergency, the field of creative arts therapies must intensify its engagement in and commitment to climate action. Creative arts therapists hold unique skills to promote positive social change, foster deep reflection and expression on the impacts of the crisis, facilitate creative problem solving, and inspire visioning and innovation for better futures. To help consider how these skills can be harnessed, the authors propose a framework that can be used across the creative arts therapies modalities and be adapted within different theoretical approaches to invite intentional climate reflection and suggest different types of action. This framework can help creative arts therapists to determine ways their professional practices can be more aligned with values of climate wellness, including their work with clients, roles as educators to participants in learning contexts, and their roles within their professional workplaces and greater communities. • Presents a foundation to attend to the climate crisis in the creative arts therapies. • Offers an original framework to support reflective and intentional engagement. • Prioritizes decolonization and systemic considerations.
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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 | 0.018 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.012 | 0.096 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".