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Record W2322086144 · doi:10.1017/s0008423914000912

Toronto-area Ethnic Newspapers and Canada's 2011 Federal Election: An Investigation of Content, Focus and Partisanship

2014· article· en· W2322086144 on OpenAlexaffabout
April Lindgren

Bibliographic record

VenueCanadian Journal of Political Science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNewspaperMainstreamPolitical scienceVotingEthnic groupFederal electionPoliticsCompetition (biology)News mediaContent analysisPublic relationsMedia biasFocus (optics)Public administrationMedia studiesSociologySocial scienceLaw

Abstract

fetched live from OpenAlex

Abstract Canada's political class is embracing ethnocultural news media with increasing zeal, highlighting the need to understand the role of these news organizations in the political process. This study investigated coverage of Canada's 2011 federal election in five Toronto-area ethnocultural newspapers. The publications, which carried campaign news to varying degrees, provided coverage that was distinct in many ways from mainstream media. Content such as the focus on ingroup candidates had the potential to strengthen community bonds while more general election news equipped readers with information that would facilitate participation in society through informed voting. Analysis of reporting about the Conservative Party of Canada, which pursued an aggressive ethnic media strategy, identified no clear pattern of stories with explicitly biased content. In most newspapers, however, the CPC did enjoy an advantage in that it received more coverage than the competition.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0030.001
Scholarly communication0.0030.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.084
GPT teacher head0.320
Teacher spread0.236 · 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 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

Citations8
Published2014
Admission routes2
Has abstractyes

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