MétaCan
Menu
Back to cohort
Record W4395483558 · doi:10.1177/2631309x241242146

Corruption in the News: Complicity in Canadian Newspaper Claimsmaking, 1980-2023

2024· article· en· W4395483558 on OpenAlexafffundabout
Karl Guebert, Steven Bittle, Jon Frauley

Bibliographic record

VenueJournal of White Collar and Corporate Crime · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsComplicityNewspaperLanguage changePolitical scienceLawMedia studiesBusinessAdvertisingSociologyArtLiterature

Abstract

fetched live from OpenAlex

This paper explores the symbolic dimension of corruption in the print media, or the rhetoric deployed that reproduces a particular discursive order. Employing an abductive materialist analysis and drawing insight from the political-economy and critical anti-corruption(ism) literatures, we examined over 2300 news items on corporate corruption in five prominent Canadian newspapers. In addition to finding differing and contradictory notions of corruption, we identify three phases of (anti)corruption rhetoric that represent notable moments in the struggle over the meaning of corruption and how to curb it. The paper concludes that Canadian newspapers have reproduced the language and claims of powerful voices emanating from the international realm rather than scrutinizing these claims, resulting in an incoherent Canadian popular discourse on corruption.

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)0.006
metaresearch head score (Gemma)0.036
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.012
Science and technology studies0.0140.007
Scholarly communication0.0100.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.304
Teacher spread0.257 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJournal of White Collar and Corporate CrimeSame topicLaw in Society and CultureFrench-language works237,207