Creative, embodied practices, and the potentialities for sustainability transformations
Bibliographic record
Abstract
Abstract This paper argues for an integrative approach to sustainability transformations, one that reconnects body and mind, that fuses art and science and that integrates diverse forms of knowledge in an open, collaborative and creative way. It responds to scholarship emphasizing the importance of connecting disparate ways of knowing, including scientific, artistic, embodied and local knowledges to better understand environmental change and to foster community resilience and engagement. This paper draws on the experience of an arts-based project in Lisbon, Portugal, and explores embodied and performative practices and their potential for climate change transformations. It puts forward and enlivens an example, where such forms of engaging communities can provide new insight into how equitable, just and sustainable transformations can come about. The process involved a series of interactive workshops with diverse arts-based methods and embodied practices to create performative material. From this process, a space emerged for the creation of meaning about climate change. Three key elements stood out in this process as being potentially important for the emergence of meaning-making and for understanding the impact of the project: the use of metaphors, embedding the project locally, and the use of creative, embodied practices. This furthers research, suggesting that the arts can play a critical role in engaging people with new perspectives on climate change and sustainability issues by offering opportunities for critical reflection and providing spaces for creative imagination and experimentation. Such processes may be important for contributing to the changes needed to realize transformations to sustainability.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".