Bringing power to place: CanWest Global Communications versus foreign media ownership limits
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".