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Record W4307124167 · doi:10.5430/elr.v11n2p8

Code-switching and the Construction of Identity in Where Are We Going, Dad? Season V from the Socio-psycholinguistic Perspective

2022· article· en· W4307124167 on OpenAlexvenueno aff
Fang Xiaoying

Bibliographic record

VenueEnglish Linguistics Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCode-switchingIdentity (music)Perspective (graphical)Code (set theory)Ethnic groupPsychologyLinguisticsFirst languageMeaning (existential)Social psychologySociologyComputer scienceAesthetics

Abstract

fetched live from OpenAlex

This study investigates the code-switching in people’s daily interaction in the outdoor parent-child reality TV show Where Are We Going, Dad? Season V from the socio-psycholinguistic perspective. The main purpose is to reveal how the social meanings of dialogues and identity construction enact in parents’ and their children’s daily interactions. Based on both quantitative and qualitative methods, this study analyzes daily conversations in different situations from three aspects, including speech accommodation, language attitude, and psychological motivation. The findings indicate that code-switching from Mandarin to English plays a more central role in the show. Moreover, code-switching used in the show is regarded as a language choice as well as a way to signify the speaker’s conscious shift of self-identity in a different situation. Language convergence denotes parents’ and their children’s adaptation to local environments and respect for local culture, meaning that speakers try to establish a common identity with the local people. Chinese and English code-switching has been associated with a shift between a soft one in Chinese and a forceful one in English, implying that there is a submissive self in Chinese and an authoritative self in English. The psychological motivation reveals the sense of belonging to the mother tongue and national identity of language users. Therefore, code-switching reveals complex ethnic identities, including the self as a show performer, cultural lover, father, or mother, which are consciously or unconsciously influenced by the speakers’ language repertoire, social background knowledge, and their intention of building ethnic identity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.008
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
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 head0.115
GPT teacher head0.513
Teacher spread0.398 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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