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Media Framing of a Scandal: The Path to Redemption or the Road to Perdition?

2023· book-chapter· en· W4384197061 on OpenAlexaffabout
Esther R. Maier, Eve Lamargot

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFraming (construction)Political scienceLanguage changeMultinational corporationMedia coveragePhenomenonMedia studiesPolitical economySociologyLawHistoryEpistemology

Abstract

fetched live from OpenAlex

Abstract This chapter explores the evolution of the media framings of a corporate corruption scandal over time. Our analysis focuses on the evolution of media frames used by the English and French Press in the coverage of the corruption scandal involving SNC-Lavalin, a Quebec-based multinational engineering firm. We reveal how media coverage shifted from balanced and nuanced coverage of a complex phenomenon that facilitated debates on the appropriate consequences of corruption to a selective (re)construction of events to serve partisan agendas when the company’s legal plight was politicized. Our study contributes to the literature on media framings of corporate corruption by highlighting how the politicization of a corporate corruption scandal led to a dual climate of opinion across the English and French Press.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.924
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.067
GPT teacher head0.311
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes2
Has abstractyes

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