Making a Cantonese‐Christian family: Quotidian Habits of language and background in a transnational Hongkonger church
Bibliographic record
Abstract
Abstract Studies of the Hong Kong‐Vancouver transnational migration network seldom pay close attention to religion in the everyday lives of Hongkonger migrants. Based on 9 months of ethnographic fieldwork at St. Matthew's Church, a Hong Kong church in Metro Vancouver, this paper examines the tacit assumptions and taken‐for‐granted quotidian practices through which a Hongkonger church is made. I argue that St. Matthew's Church has been constructed as a Hong Kong Cantonese‐Christian family space through the everyday use of language and invocations of a common educational background. This argument extends the literature on Hongkonger migration to Metro Vancouver by grounding it in a religious site whose intersections with Hong Kong migration to Vancouver consolidates the church as a religious mission with a specifically Hongkonger migration narrative. This consolidation is problematised as I show that contestations in church life by migrants from the People's Republic of China over language and asymmetrical educational backgrounds both reinforce and challenge the church as a Hongkonger congregation. Through an examination of these everyday interactions at St. Matthew's Church, this paper advances the geography of religion as I demonstrate that specific geographical narratives and networks shape quotidian practices in religious sites. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".