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Record W2003140875 · doi:10.1177/1746197913483635

Citizenship education and diversity in liberal societies: Theory and policy in a comparative perspective

2013· article· en· W2003140875 on OpenAlexaboutno aff
Mikael Sundström, Christian Fernández

Bibliographic record

VenueEducation Citizenship and Social Justice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipSociologyDiversity (politics)DemocracyCitizenship educationPerspective (graphical)Variety (cybernetics)Resistance (ecology)PhenomenonSocial sciencePolitical sciencePedagogyPublic administrationEpistemologyPoliticsLaw

Abstract

fetched live from OpenAlex

Citizenship education is a popular and contested phenomenon in liberal democratic societies. It is difficult to imagine a school system that does not contribute to the preservation and improvement of society through education of democratic, responsible and tolerant citizens. On the contrary, the execution of such education is full of caveats, controversy and resistance. This special issue examines the inherent tensions of citizenship education in a variety of national contexts (France, England, Sweden and Quebec) and from several theoretical and empirical perspectives. In this introductory article, we present an overview of the debates on citizenship education in academia and the media and propose a conceptual framework for the categorisation and comparison of the diversity of practices that relate to citizenship education. This model is then used to guide a brief presentation of the remaining articles in the special issue.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.007
Science and technology studies0.0100.064
Scholarly communication0.0170.009
Open science0.0010.006
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.368
Teacher spread0.330 · 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 designTheoretical or conceptual
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

Citations13
Published2013
Admission routes1
Has abstractyes

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