Bibliographic record
Abstract
There is strong evidence that both music training and physical exercise are associated with various cognitive abilities. Musicians tend to have superior auditory memories compared to non-musicians, and physical activity is associated with working memory. In dance, these two areas are combined, but very few studies have examined links between dance training and cognitive skills. Dancers are required to remember long complex patterns of body movements over time, an ability that is practiced in most trained dancers. This study examined the association between dance training and memory skills. University students with varying amounts of dance experience were recruited, and they completed measures of visual and auditory memory, general intelligence, and personality. Consistent with previous research, extracurricular physical activity was associated with our working memory measures. Music training was initially associated with auditory immediate memory, but this disappeared when controlling for IQ and the personality variable of openness. By contrast, duration of dance training was associated with visual memory but not auditory memory. These findings were what was expected due to dance’s heavy reliance on visuals; dance may benefit visual memory or people with better visual memories may be more likely to participate and stay in dance training. These results demonstrate that different classes of extracurricular activities are associated with different aspects of memory. Discipline: Psychology (Honours) Faculty Mentor: Dr. Kathleen Corrigall
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.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.006 | 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".