Ep. 221 - Indie Journalists On The Government News Bailout
Bibliographic record
Abstract
After two years of reports and stuffy consultations, the slow-moving train-wreck that's been the "news bailout" has made its way into the proposed 2018-19 federal budget. The budget dedicates $50 million dollars over five years to "supporting local journalism," but who's eligible for funding? Though crucial details are pending, PostMedia Network's CEO Paul Godfrey and former Globe and Mail EIC Ed Greenspon are not happy—so maybe this isn't such a bad thing after all! Jesse speaks with entrepreneurs running innovative, independent digital media startups across the country to gauge their reactions, and to see if any of them will be vying for a piece of the government-made pie. Maureen Googoo of Ku'Ku'Kwes News (Atlantic Canada), Tim Bousquet of The Halifax Examiner (Halifax), Erin Millar of Discourse Media (Vancouver), Jeremy Klaszus of The Sprawl (Calgary), and James Baxter of iPolitics (Ottawa) join Jesse.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.094 | 0.016 |
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; both teacher heads agree on what is shown here.
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".