Bibliographic record
Abstract
Citing “national security” is a catch-all defence for governments justifying repressive actions against journalists who are probing incompetence, corruption and malfeasance by the state. For governments its merit is that it trades on the mystique and unknowability of the world of intelligence, where the public accepts there are some matters that only government can judge. However it frequently abuses a fundamental: The political contract between the people and the state whereby the citizen surrenders certain rights to government in return for security. Frequently drawing on the author&s;s own experiences as a journalist, the chapter covers matters such as the Spycatcher affair, the repeated attempts to toughen the Official Secrets Act so as to deter further whistle-blowers, the use of the Islamicist terror threat in order to increase the frequency of the use of the “national security” justification for censorship in many jurisdictions, and the publication by The Guardian of classified documents leaked by former National Security Agency (NSA) contractor Edward Snowden, which revealed that the eavesdropping agencies of the US, UK, Australia, Canada and New Zealand had acted illegally. The paper was threatened by the government and attacked by government-supporting newspapers and the intelligence lobby for allegedly undermining national security. The chapter argues that such responses to revelations of official wrongdoing make the media&s;s role as a watchdog guarding the public interest well-nigh impossible. This pattern is repeated in many countries, and the result is the growth of unfettered national security states in which the fourth estate has all but lost its investigative capability.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.243 | 0.151 |
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".