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Record W4403642302 · doi:10.15845/bells.v14i1.4340

A comparison of Heritage vs Homeland Taiwanese Mandarin speaker attitudes towards sajiao

2024· article· en· W4403642302 on OpenAlexaff

Bibliographic record

VenueBergen Language and Linguistics Studies · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMandarin ChineseHomelandHeritage languagePsychologyLinguisticsSpeech recognitionPolitical scienceComputer sciencePedagogyPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.069
GPT teacher head0.378
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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