Will you dance with me, Dr E? Empowering early childhood practitioners through dance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dance education in preschool has been linked to many benefits for children’s development. However, research shows that practitioners often lack the confidence to implement such activities, as they feel they are missing substantial knowledge in this area. This paper aims to address this issue and empower practitioners to use dance as an essential tool in their teaching practice. The project did not aim to teach specific dance styles but to support practitioners to use dance as a collaborative process with children, giving them a voice. The intervention took place in four preschool classrooms over four months in South-East London. 18 practitioners participated, using the Dancing with Dr E framework on a weekly basis. Practitioners had no previous experience in dance. The intervention took place for 20–30 mins, three times per week but this was flexible. The outcomes of the intervention were measured with a short questionnaire and semi-structured interviews. Findings demonstrated the benefits of the dance intervention for practitioners’ well-being and confidence, providing opportunities for self-reflection, mindfulness, and following a child-led methodology. The sustainability of the project was confirmed, as practitioners planned to integrate it into their future practices in various ways, supporting the community and reaching a wider audience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it