Dramatising the shock of the new: using Arts-based embodied pedagogies to teach life skills
Bibliographic record
Abstract
The digital economy and the global pandemic, together with the effects of climate change, have taken a human toll affecting the pace of everyday life, creating an exponential increase in anxiety and stress related diseases. Today’s complex, globalised world creates a need to challenge and reconceptualise educational priorities. In an increasingly polarised world of beliefs and values, with a rise in populism and nationalism, empathy is essential. In order to function successfully, one needs to know who people are, and the whys and wherefores of their actions and beliefs. This article focuses on how the Arts and humanities can teach a new generation of life skills necessitated by our globalised society and the socio-political aspects of immigration. It discusses how embodied pedagogies help develop self-awareness, emotional regulation and affective empathy and reduce stress. The authors present Arts-based pedagogies and educational strategies that bring history, cultures and beliefs alive and help counteract hatred, tribalism and racism and the illusion of ‘us and them.’ The article examines what these changes in pedagogy can offer to the discourse, both in the need to keep body/mind healthy and acquisition of new skills necessary for adapting to a changing global environment and cultural /political landscapes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".