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Record W2916530830 · doi:10.22230/cjc.2019v44n1a3321

The Representation of Women and Racialized Minorities as Expert Sources On-Air in Canadian Public Affairs Television

2019· article· en· W2916530830 on OpenAlexaffvenueabout
Wendy Cukier, Samantha Jackson, Suzanne Gagnon

Bibliographic record

VenueCanadian Journal of Communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsMcGill UniversityToronto Metropolitan University
Fundersnot available
KeywordsDisadvantagedRepresentation (politics)CorporationPublic broadcastingPolitical scienceGender studiesRace (biology)Broadcasting (networking)SociologyAdvertisingLawBusinessPoliticsComputer science

Abstract

fetched live from OpenAlex

Background Research shows that women and racialized minorities are misrepresented and underrepresented across popular media. To date, however, limited attention has been given to the representation of these groups as expert news sources within Canadian television. Analysis This study conducts an analysis of three public affairs shows aired by the Canadian Broadcasting Corporation and the Ontario Educational Communications Authority over a four-month period, cataloguing the gender and racialized minority status of 737 on-air guests. Conclusions & implications The findings show that women and racialized minorities are underrepresented, with racialized minority women being particularly disadvantaged.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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 designNot applicable
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

Citations12
Published2019
Admission routes3
Has abstractyes

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