Sensorial Contemporary Arts, Mindfulness and Play for Children's Post‐Pandemic Recovery – Qualitative Evaluation of <i>The Children's Sensorium</i>
Bibliographic record
Abstract
Abstract ‘The Children's Sensorium – art, play and mindfulness for post‐pandemic recovery’ was an exhibition that brought together sensory‐based art installations featuring First Nations Connection to Country with mindfulness and embodiment strategies to enhance well‐being for children (ages 4–11). As the COVID‐19 pandemic slowly moves from the centre of public attention, we are starting to gauge the impact of the world's longest lockdown in Melbourne, Australia, on children's well‐being and resilience. ‘The Children's Sensorium’ exhibition was created with children and their well‐being in mind. In this article, we focus on insights from the exhibition evaluation and address the ways artistic and sensory‐based mindful engagement can support children's well‐being and resilience. Evaluation of The Sensorium exhibition provides a view into the potential of sensory‐based artworks to create a stimulating environment, positive emotions, mindful awareness of their senses and the environment and a sense of playful agency for children. The Sensorium provoked a fresh way of thinking about art exhibitions for children: one that centred a child‐friendly, strength‐based artistic space where children felt agency to be creative and explore the complexity of their emotions, hopes and fears in the wake of the global pandemic.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".