Perceived benefits of choral singing : social, intellectual, and emotional aspects of group singing
Bibliographic record
Abstract
This research sought to explore the meaningfulness of belonging to a choir. Members of 14 Canadian choirs (N=404) responded to 18 statements concerning the perceived benefits of choral singing. Choristers ranked six aspects of choral singing in the following order of importance (from greatest to least): musical, intellectual, emotional, physical, social, and spiritual. An in-depth analysis of three central areas of the choral experience (social, intellectual, and emotional) was done and six sample populations were compared: paid vs. volunteer choristers, choristers living in different areas (urban, suburban, and rural), choristers with a music degree vs. non-degree, age of choristers (young adult, middle-aged, and senior), choir size (large, medium, and small), and type of choir (community and church). Results showed that choristers in small choirs felt like valued members of their choirs, felt a positive connection with the other choristers, and that singing in choir raised their mood to a significantly higher degree than choristers in medium and large choirs. Significant findings showed that volunteer singers, to a greater extent than paid singers, found that choir raised their mood, helped them to relax, and was a satisfying experience which gave them a sense of accomplishment. The differences in responses between middle-aged and senior choristers were minimal, but both gave responses that were significantly higher when compared with young adult choristers. The older singers felt that singing in choir raised their mood, helped them to relax, provided them with a sense of accomplishment, and that there was a sense of unity within their choir more so than young adults.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".