The Routledge Handbook of Developments in Digital Journalism Studies
Bibliographic record
Abstract
A paradigmatic shift is sometimes revealed by an unanticipated and extraordinary event, and so it was with Edward Snowden in 2013. A National Security Agency (NSA) contractor, Snowden was so appalled at the exponential expansion of covert digital surveillance that he decided it was his moral duty to inform the public, indeed the world. This he did from a hotel room in Hong Kong when he gave a small group of selected journalists access to 1.7 million classified documents taken from the NSA. These documents revealed the global snooping capabilities of the NSA and its ‘Five Eyes’ intelligence agency partners (ASIO in Australia, CSE in Canada, GCSB in New Zealand, and the GCHQ in United Kingdom). The Five Eyes can vacuum up just about all digital communications anywhere, anytime, and much else besides if they are so minded. Many who take a deep interest in signals intelligence thought these Anglo-Saxon agencies had probably increased their capabilities since 9/11, but even they were shocked when Snowden revealed the sheer scale – it far exceeded any estimate of capability.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.069 | 0.037 |
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".