Bibliographic record
Abstract
In 2014, when Postmedia acquired Quebecor's Sun Media newspaper and online assets, there was a sense that the recent history of newspapers was repeating itself not as comedy or tragedy, but as eulogy. Crash to Paywall shows that while the newspaper business was weakened by decreases in advertising revenues and circulation, much of its problems stem from self-inflicted damage and business practices dating back to the 1970s. Brian Gorman explores the Canadian newspaper industry crisis and the relationship between the news media and the public. He challenges both the popular mantra that a "perfect storm" of unforeseen circumstances blindsided a declining industry and the narrative that readers were abandoning newspapers, causing advertisers to turn away from "dying" media. Gorman argues that observers had been warning for decades that the business was creating its own problems by acquiring ever-larger debt and shareholder obligations while steadily cutting back on journalists' resources. Finally, by providing journalism for free online, newspaper companies devalued their most important resource and impaired their profitable print products. With dozens of interviews conducted with leading Canadian journalists and editors, Crash to Paywall brings to light the many misconceptions, generalizations, omissions, and highly suspect conclusions about the present state of newspapers and their future.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.093 | 0.021 |
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".