Congregational Singing as Social Identity Shaping in Toronto Cantonese Worship Services
Bibliographic record
Abstract
Congregational singing is widely acknowledged as a doxology to God. Yet, opinions differ on how congregational singing influences the worshippers’ lives. Some believe that the group singing prepares the heart for the sermon, while others believe it has formational implications. This project explores the formative qualities in congregational singing, specifically emphasizing how such group activity informs the worshipper’s identity with God and how the worshipper relates to others through God. Biblical identities are utilized as the theological perspective to examine the identity messages expressed in congregational singing. The idea of identity hierarchy in social psychology, which includes social association and identity renegotiation, is used as the theoretical framework. This research strives to conduct critical inquiry and reflection on the theological, theoretical, and practical orientation of congregational singing in Greater Toronto Area Cantonese worship services. As such, a literature review concerning the theology, theory, and practice of congregational singing is discussed, from which implications are drawn to the research design process. Participant observation, online questionnaire, and qualitative interview methods are used to help extract and analyze how the social identity shaping process occurs in congregational singing within the research context.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".