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Record W2889551447 · doi:10.1386/ctl.13.2.193_1

Good person, good citizen? The discourses that Chinese youth invoke to make civic and moral meaning

2018· article· en· W2889551447 on OpenAlexaff
Xin Xiang, Xu Zhao, Siwen Zhang, Ashley Lee, LI Yi-yu, Helen Haste, Liu Zhi, Megan Cotnam-Kappel

Bibliographic record

VenueCitizenship Teaching and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of OttawaUniversity of Calgary
Fundersnot available
KeywordsAction (physics)Meaning (existential)Causality (physics)SociologyPower (physics)PerfectionNarrativeChinaPosition (finance)EpistemologyEnvironmental ethicsPublic relationsSocial psychologyPolitical scienceLawPsychology

Abstract

fetched live from OpenAlex

Abstract In a time of transition, China is formulating principles for moral and civic responsibility and action that will serve the new goals for an expanding world power. How do young Chinese people define the ‘good person’ and ‘good citizen’, and the qualities to which they should aspire, in this changing climate? How do these mesh with the public messages and the historical traditions from which they derive? Using discourse analysis we report data from 8th and 11th grade students in Shanghai and Nantong that reveal four discourses around civic and moral responsibilities, norms and goals. Discourse analysis enables us to identify the underlying explanatory narratives that attribute causality and consequence, position people and institutions, imply judgements and values, and prescribe acceptable or expected actions. The four discourses are (1) Obeying Rules and Laws; (2) Building and Maintaining Relationships; (3) Striving towards Moral Perfection and High ‘Quality’; and (4) Loving One’s Country and Contributing to Society.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.328
Teacher spread0.278 · 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.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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