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Record W2167778312

PROMOTING CIVIC ENGAGEMENT THROUGH ETHNIC MEDIA

2010· article· en· W2167778312 on OpenAlexaboutno aff
Sherry S. Yu, Daniel Ahadi

Bibliographic record

VenuePlatform Journal of Media and Communication · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupMainstreamCitizenshipMulticulturalismPoliticsImmigrationPolitical scienceCivic engagementGender studiesSociologyPublic sphereMedia studiesLaw
DOInot available

Abstract

fetched live from OpenAlex

Ethnic media, defined by the Canadian Radio-television and Telecommunications Commission (for the ethnic program specifically) as “one, in any language, that is specifically directed to any culturally or racially distinct group other than one that is Aboriginal Canadian or from France or the British Isles” (CRTC, 1999), are emerging to offer new communicative civic spaces to ethno-cultural citizens. Studies, however, suggest that while they may not be completely disconnected from broader society, they remain largely “distinct from the dominant public sphere” (Karim, 2002). The majority are focused on a single ethnic group and develop in isolation of each other to cater to their specific group’s interests. Such an isolationist tendency is a concern in multicultural societies in that it can potentially intensify political, socio-economic, and cultural divides among older and new populations and develop “parallel societies” (Hafez, 2007) and a fragmented citizenship. Whether or not ethnic media will lead to hindering immigrants’ civic integration by raising citizens of communities rather than citizens of the broader society needs to be empirically validated. This paper, therefore, explores the distinction between mainstream and ethnic media through a comparative content analysis on coverage of the October 14 2008 Canadian federal election in English and Korean press in British Colombia, Canada. The findings suggest that in-group orientation is in fact more distinct in English media with significantly low attention given to ethnic minorities either as candidates or voters. Ethnic media, on the other hand, undertake significant citizenship education by delivering step-by-step “how-to” information about the election to immigrants who are less familiar with the Canadian political system to assist them in exercising voting rights.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.102
GPT teacher head0.369
Teacher spread0.267 · 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

Citations23
Published2010
Admission routes1
Has abstractyes

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