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Record W2121474814 · doi:10.1123/japa.11.1.123

Characteristics, Enrollment, Attendance, and Dropout Patterns of Older Adults in Beginner Tai-Chi and Line-Dancing Programs

2003· article· en· W2121474814 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Aging and Physical Activity · 2003
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAttendanceDropout (neural networks)PsychologyRecreationGerontologyDemographyMedicineSociology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.279
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it