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Record W3039911848 · doi:10.22230/cjc.2020v45n2a3561

Enabling Postmedia: Economists as the “Rock Stars” of Canadian Competition Law

2020· article· en· W3039911848 on OpenAlexvenueaboutno aff
Marc Edge

Bibliographic record

VenueCanadian Journal of Communication · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperCompetition (biology)Political scienceMedia coverageNews mediaCompetition lawBusinessAdvertisingLawEconomicsMedia studiesMarket economySociologyMonopoly

Abstract

fetched live from OpenAlex

Background Canada is suffering a crisis in local news largely attributable to regulatory failure. Its largest newspaper chain, Postmedia Network, took over the second-largest chain in late 2014, and in early 2016 it merged the newsrooms at its duplicate dailies in four of Canada’s six largest cities. Parliamentary hearings on local media ensued, and a mid-2017 report recommended, among other things, changes to the Competition Actto more effectively deal with news media mergers and takeovers. Analysis The Competition Bureau is dominated by economists who may lack sufficient grounding in media issues to effectively deal with mergers and takeovers in news industries. Conclusion and implications Reform of the country’s Competition Act, which has been called for by successive federal media inquiries, is more urgently required than ever.

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)0.010
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.847
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0210.032
Scholarly communication0.0250.010
Open science0.0020.005
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0200.001

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 head0.035
GPT teacher head0.264
Teacher spread0.229 · 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 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

Citations1
Published2020
Admission routes2
Has abstractyes

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