How the Camel Got in the Tent: The Canadian Assault on Australia's Foreign Media Ownership Limits
Bibliographic record
Abstract
Before 1991, Australia enforced strict limits on foreign ownership of licensed broadcasters and also limited foreign ownership of newspaper publishers. In the early 1990s, however, a pair of Canadian entrepreneurs succeeded in first raising and then circumventing those limits. Conrad Black bought 15 per cent of the Fairfax newspaper chain in 1992, and shortly before the ensuing national election lobbied to increase his stake to 25 per cent. In his 1993 autobiography, Black described backroom political dealings that resulted in a Senate inquiry. The Australian Broadcasting Authority soon began an investigation into another Canadian challenging the country's foreign media ownership limits. Israel ‘Izzy’ Asper, a former tax lawyer, found a way to legally purchase 57.5 per cent of Network Ten in 1992 by holding 42.5 per cent in the form of non-voting debentures. The ABA absolved his CanWest Global Communications of controlling Network Ten in 1995. Non-voting shares were outlawed in 1997, but CanWest was allowed to retain its debentures. The inquiries into Canadian purchases contributed to a decade-long process of re-evaluating media ownership limits that resulted in restrictions on foreign ownership being eliminated in 2006.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".