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Record W1758240768 · doi:10.3968/4737

Educating for Democratic Citizenship in a Globalizing World: Some Recent Developments in England and China

2014· article· en· W1758240768 on OpenAlexvenueno aff
Yiming Ren

Bibliographic record

VenueHigher education of social science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipChinaDemocracyCurriculumStrengths and weaknessesPolitical scienceCitizenship educationNational curriculumSociologyPublic administrationEconomic growthLawEconomicsPsychology

Abstract

fetched live from OpenAlex

This paper compares the development of education for democratic citizenship in two apparently diverse nations - China and England - at different moments in their social and economic histories, but both in the process of ‘re-identifying’ themselves globally. It is suggested that, for all their differences, there is sufficient in common between the two nations in terms of how democratic citizenship is perceived and of what might constitute an appropriate education for democratic citizenship for useful inter-national dialogues and exchanges to be initiated between scholars and practitioners in the two countries. The longer experience of a formal citizenship education curriculum in England, including its strengths and weaknesses, are likely to be of help to Chinese scholars, teachers and policymakers in this area, especially given the current piecemeal nature of the design and implementation of citizenship programmes in China; while the ‘fresher’ approach to developing citizenship education programmes by enthusiastic scholars, teachers and policymakers in China is likely to throw fresh light on how citizenship is understood and ‘taught’ in England.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.368
Teacher spread0.337 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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