Using technology to enhance and encourage dance-based exercise
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
This study investigated the role of Self-Service Technologies (SSTs) in dance-based exercise in order to begin exploring the motivations behind the use (or not) of SSTs by ordinary men and women in this context. The research approach employed interviews to gain insights into participants' use of SSTs and their exercise practices, in order to start establishing ways in which dance can be re/incorporated into people's lives through the design of appropriate SSTs. Findings from this study highlight the significant opportunity to further explore how the properties of music and dance can be integrated into the design of new SSTs. Literature suggests dance could be a beneficial exercise format for many people and self-service technology abounds for exercise but is often not used consistently. Our interviews asked participants about dance-based exercise and SSTs for exercise and showed that there is an opportunity to design SSTs to help people access dance-based exercise. SSTs should help people learn dance, build confidence, and dance alone or with others. SSTs could facilitate movement and increase engagement with physical activity whilst addressing issues around logistics, confidence and dance knowledge and experience.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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