Facebook's Zuckerberg urged to testify before 'grand committee'
Bibliographic record
Abstract
Parliamentary committees in Britain and Canada are urging Facebook CEO Mark Zuckerberg to testify before a joint hearing of international lawmakers examining fake news and the internet. Facebook CEO Mark Zuckerberg is being urged to testify before a joint hearing of international lawmakers examining fake news and the internet.The head of the U.K. parliament's media committee, Damian Collins, is joining forces with his Canadian counterpart to pressure Zuckerberg to personally take part in hearings, as he did before the U.S Congress and the European Parliament.Collins says the November 27th session will be hosted by an "international grand committee," and he says it's likely other parliaments will be represented.Facebook's Mark Zuckerberg is being urged to testify before a joint hearing of international lawmakers. Parliamentary committees in Britain and Canada want Zuckerberg to take part. UK parliament's Damian Collins says the session will be hosted by an 'international grand committee'
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.109 |
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".