Bibliographic record
Abstract
This book is about three overlapping crises: the crisis that has enveloped the CBC, the crisis of news, and the crisis of democracy.They are all the result, to some degree, of the vast changes that have overtaken and consumed the media world in the last 10 to 15 years.The emergence of platforms such as Google, Facebook, Twitter, and Netflix; the hypertargeting of individual users through data analytics; the development of narrow, online-identity communities; and the blast of an attention economy that makes it more and more difficult for any but the most powerful media organizations to be noticed have changed the media landscape in dramatic ways.The effects on the CBC and on other Canadian media organizations have been shattering.To put it bluntly, news and journalism are in a deep crisis, for reasons that we will explain in considerable detail in the book.Our argument is that the CBC, Canada's public broadcaster, has reached a crossroads.Years of budgetary uncertainty, a lack of policy vision by governments and by the CBC itself, and the brutality of the attention economy have taken a toll.For the CBC, the choices are stark.The public broadcaster will either be reimagined and reinvented or die a slow death on the outskirts of the media world.We suggest a way of going forward that would transform much of news and, as a consequence, public affairs in Canada.We could not have undertaken this journey without help from others.We are indebted to the scholars who have paved the way in studying public broadcasting in Canada and Canadian media.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.407 | 0.253 |
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".