Cultural Crash: Public Service Broadcasters During the Great Depression and the Late 2000s Recession
Bibliographic record
Abstract
In October 2009, the Canadian Broadcasting Corporation (CBC) announced that it would greatly revamp its news services (McGuire, 2009); similarly, in January 2010, the Australian Broadcasting Corporation (ABC) announced that it would add a 24-hour digital news channel (ABC News, 2010). These declarations precipitated significant shifts in the Canadian and Australian media landscapes. These public service broadcasters initiated major news restructurings following one of the worst global financial crises since the Great Depression. In late 2008, the Bank of Canada declared that Canada was entering a global recession (Pingue, 2008), and in mid-2009, Statistics Canada data revealed that Canada’s recession was over (Corcoran, 2009). By contrast, Australia, in large part, avoided recession—defined as two consecutive cycles of shrinking gross domestic product (GDP)—as the government quickly responded to the global downturn (Stanford, 2009). Due to the wide reach of this economic crisis and Australia’s reliance on other national economies, the Australian government provided grand stimulus packages. While Australia’s stimulus injection was massive and prompt, Canada’s initial response was lacking and lagged. The global nature of this crisis also challenged the abilities of English-language national
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".