Chapter 1. Language socialization into Chinese language and “Chineseness” in diaspora communities
Bibliographic record
Abstract
Language socialization research provides a rich, socioculturally-oriented theoretical framework and set of analytic tools for examining the experiences of newcomers and other novices learning language in a range of educational settings, both formal and informal. This chapter first presents an overview of language socialization principles and then highlights several personal narratives of language socialization within Chinese diaspora communities in different geographical settings. Next, studies on Chinese heritage-language socialization are examined with a focus on the functions and forms of codeswitching, shaming, narrativity, the socialization of taste during meals, and literacy texts in traditional Chinese diaspora homes as well as in ethnically mixed or blended ones. The chapter recommends, in closing, that future research should examine to a greater extent continuities, discontinuities, syncretism, and innovations in Chinese language learning and use across home, school, and community settings and across multiple timescales in order to better understand the relationship between being and knowing/using Chinese in contemporary societies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".