'BradCast' 10/28/2024 (Ballots Burn in WA, OR; Billionaire WaPo, LATimes owners 'Obey in Advance')
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
On today's 'BradCast':Â The FBI is investigating ballot drop boxes in Portland, OR, Vancouver, WA that were set on fire, destroying hundreds of ballots, in apparent arson incidents. Philadelphia's district attorney sued billionaire Elon Musk to halt his 'lottery' giveaway as a likely unlawful vote-buying scheme. The billionaire owners of the Washington Post and Los Angeles Times cited flimsy excuses for killing their papers' planned endorsements of Kamala Harris for president, in turn triggering warnings from experts in fascism that the outlets have succumbed to 'obeying in advance,' kowtowing to a wannabe dictator who's not even in office yet. Callers weigh in, and offer their own endorsements in the last days before the pivotal 2024 presidential election.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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 it