A comparison of Heritage vs Homeland Taiwanese Mandarin speaker attitudes towards sajiao
Bibliographic record
Abstract
This study investigates the language attitudes and perceptions of Taiwanese Mandarin heritage and homeland listeners towards the use of sajiao, a stylized speech type, in two varieties of Mandarin. A matched guise experiment was conducted via Qualtrics with heritage listeners from the United States (n = 6) and homeland listeners from Taiwan (n = 7). Participants listened to a recording and rated their perceived social constructions of the speakers in terms of their cuteness, pleasantness, femininity, masculinity, and professionalism on a scale from one to seven. In total, participants listened to 130 recordings, 64 target and 66 filler, of 4 different sentences with both sajiao and non-sajiao forms. We find that heritage speakers pattern similarly to homeland speakers, although not to the same extent. This positions heritage speakers in their own category, where they have acquired the social associations with this specialized speech style, but not to the same degree as homeland speakers. This research sheds new light on heritage language socialization and perceptions of language variation, namely regarding two varieties of Mandarin and speech style. Further research is needed to investigate how Beijing Mandarin heritage speakers would perform in this same task.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".