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Record W429281332

Bringing power to place: CanWest Global Communications versus foreign media ownership limits

2008· article· en· W429281332 on OpenAlexaboutno aff
Marc Edge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsMedia conglomeratePoliticsForeign ownershipPublic broadcastingDeregulationOrder (exchange)Power (physics)Political scienceBroadcasting (networking)DivestmentAdvertisingBusinessEconomicsLawMarket economyFinance
DOInot available

Abstract

fetched live from OpenAlex

CanWest Global Communications is an international media company based in Canada and controlled by a family of lawyers. Established with one television station in 1975, CanWest expanded across Canada over the next 15 years. In 1991, it took advantage of media ownership deregulation in New Zealand by acquiring and turning around the foundering TV3 network. The following year, it acquired 57.5 percent ownership of Australia’s Network TEN, a holding well in excess of that country’s 15 percent limit on foreign ownership of television broadcasters. An ingenious arrangement, however, allowed CanWest to retain its majority ownership, but only after a 1995 inquiry by the Australian Broadcasting Authority cleared it. The ABA did order CanWest two years later to divest an additional 19 percent of TEN shares it subsequently acquired control over. CanWest’s dealings in Australian media contributed in part to a long-running debate in Australia over foreign ownership limits that culminated with such restrictions being lifted in 2006. Political interference in their media holdings by the owning family in Canada should give cause for concern in Australia. A number of strong political positions, including fiscal conservatism, uncritical support for Israel, the abolition of public broadcasting, and neoliberalism generally have been promoted in their Canadian media holdings.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.136
GPT teacher head0.356
Teacher spread0.221 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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