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Record W2289719048 · doi:10.18251/ijme.v18i1.1091

Civics Is Largely About Politics: The Possibilities and Challenges of a Citizenship Education Pedagogy that Embraces Democratic Politics and Recognizes Diversity

2016· article· en· W2289719048 on OpenAlexaffabout
Luz Alison Molina-Girón

Bibliographic record

VenueInternational Journal of Multicultural Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCivicsCitizenshipPoliticsDiversity (politics)MulticulturalismDemocracyPedagogySociologyMulticultural educationCitizenship educationSocial studiesBiology and political orientationPolitical scienceLaw

Abstract

fetched live from OpenAlex

Research investigating the practice of citizenship education in multicultural schools is scarce. Drawing on classroom observations and teacher and student interviews in four multicultural Grade 10 Civics classrooms in Ottawa, Canada, this case study discusses one teacher’s unique citizenship education pedagogy, an approach that embraces democratic politics and affirms diversity. Vignettes of class instruction illustrate the teaching strategies implemented and the struggles faced in employing this pedagogical approach. The case study contends that a critical multicultural citizenship education must have a strong political orientation and, additionally, be responsive to the existing social and cultural diversity that defines our democratic community.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.167
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.119
GPT teacher head0.394
Teacher spread0.275 · 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 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
Published2016
Admission routes2
Has abstractyes

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