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Record W4289775958 · doi:10.18192/cjmsrcem.v16i1.6454

Conspiracy to Commit Murder? Canadian Newspaper Trades and Closures, 2010-2017

2018· article· en· W4289775958 on OpenAlexvenueaboutno aff
Marc Edge

Bibliographic record

VenueCanadian Journal of Media Studies · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperCompetition (biology)Consolidation (business)CollusionClosing (real estate)AdvertisingCommitBusinessPolitical scienceLawFinance

Abstract

fetched live from OpenAlex

Newspaper companies in both Eastern and Western Canada have engaged in anti-competitive behaviour since 2010 by exchanging titles, increasingly through trades, and then closing them to create more lucrative local monopolies. This phenomenon reached its height in late 2017 when the country’s two largest chains, Postmedia Network and Torstar Inc., traded 41 mostly Ontario titles and closed almost all of them. The chains claimed there was no collusion involved, but a Competition Bureau investigation reportedly found detailed memos and non-compete agreements. The British Columbia chains Black Press and Glacier Media also engaged in this type of consolidation in the first half of the decade without legal consequence. Including non-daily community newspapers, Black Press and Glacier Media closed or merged twenty-four of the thirty-three titles they exchanged from 2010-2014, or a competitor one of them already owned. While this would appear to be classic anti-competitive behaviour, their dealings went without investigation by the Competition Bureau. This points up the laxity of Canada’s antitrust laws in dealing with newspaper mergers and takeovers.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.167
GPT teacher head0.253
Teacher spread0.086 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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