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Record W3085033116 · doi:10.1177/1749975520947852

A Spectacle of Silencing: A Rural African-Canadian Woman’s Media Trial

2020· article· en· W3085033116 on OpenAlexaffabout
Laura Stalker, Patricia Cormack

Bibliographic record

VenueCultural Sociology · 2020
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsSpectacleAlternative mediaRuralitySociologyMiddle classLotteryMedia studiesPolitical scienceGender studiesLawRural area

Abstract

fetched live from OpenAlex

This thematic case study explores international, national, and local media coverage of a conflict between Barb Reddick, a rural, working-class, African-Nova Scotian woman, and her nephew over the ownership of a winning ‘Chase the Ace’ lottery ticket. Beginning from general media valuation of lottery winners, and Canadian coverage of the Nova Scotia CTA lottery ‘craze’, we find when Reddick goes off script as loving aunt she is pathologized and degraded in a dramatic reversal from soft to hard news story. Reddick’s habitus and trust in journalists to support her counternarrative became the dramatic content of media spectacle-making – what we call a ‘spectacle of silencing’ – as well as her deviance from Canadian white rurality, and class and gender norms. Rather than mere ‘misrepresentation’ of minorities, we conclude that the dynamics of counternarrative struggle are embedded in reportage itself as spectacle, reproducing the legitimacy and authority of journalistic institutions through a symbolic violence of consensus making.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0490.014
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.177
GPT teacher head0.384
Teacher spread0.207 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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