Characteristics, Enrollment, Attendance, and Dropout Patterns of Older Adults in Beginner Tai-Chi and Line-Dancing Programs
Bibliographic record
Abstract
The article profiles older adults who join Tai Chi and line-dancing beginner classes. Enrollment, attendance, and dropout patterns of 41 classes from 8 recreation and senior centers and 4 Taoist Tai Chi societies were tracked over a full calendar year. Enrollment was highest in the fall. Average attendance over the 8- to 12-week sessions was 72% for Tai Chi and 68% for line dancing; average dropout rates were 23% and 10%, respectively. Entry surveys and exit interviews were completed by 221 and 107 participants, respectively. Older adults who join these community classes tend to be predominantly women, Caucasian, in their mid-60s, relatively healthy, and physically active. Most in Tai Chi joined for fitness and health, whereas many line dancers joined for social reasons. Although the classes were designated as beginner classes, participants varied in level of experience. Continued participation was related to expectations, past experience, and perceived ease of learning the movements.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".