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Record W2151068583 · doi:10.20355/c56k5x

Sites for Discussion, Citizenship Education and Pathbuilding: Challenging the Fear of Controversy in the Adult EAL Classroom

2010· article· en· W2151068583 on OpenAlexaffvenueabout
Tara Gibb

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCitizenshipFeelingImmigrationCitizenship educationSociologyPedagogyGood citizenshipWork (physics)Public relationsPolitical sciencePsychologySocial psychologyLaw

Abstract

fetched live from OpenAlex

This paper explores an integrated approach to citizenship education through English-as-an-Additional Language (EAL) instruction for adults who are new immigrants to Canada. Teaching for citizenship and participation in Canadian democractic processes sometimes involves discussing non-consensual issues such as same-sex unions, human rights, and religious freedoms. The result is discussions that can be fraught with conflict and tension, posing challenges and feelings of unease for teachers and learners. Therefore, an integrated approach to citizenship education also requires considering theories on dialogue and communicative engagement. Following a discussion on issues of citizenship education for newcomers to Canada and the possibilities of an integrated citizenship program, this paper concludes with a brief exploration of the work of Gloria Anzaldua and Susan Bickford for inspiration on ways to engage with non-consensual issues that pose challenges for EAL learners and teachers.

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)0.013
metaresearch head score (Gemma)0.012
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 score0.089
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0620.049
Scholarly communication0.0250.015
Open science0.0030.026
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0080.001

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 head0.043
GPT teacher head0.437
Teacher spread0.394 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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Same venueJournal of Contemporary Issues in EducationSame topicMultilingual Education and PolicyFrench-language works237,207