Bibliographic record
Abstract
The US's adoption of the broad doctrine of `information operations' (IO) in 2003 put information and media strategies on a par with conventional means of military power and made them pivotal to achieving `full-spectrum dominance'. This article focuses on the role of IO in shaping the global media ecology and in the battle for hearts and minds, especially in Muslim-majority countries. However, the author also argues that the impact of such operations at home may be their most important legacy. IO `blowback' occurs as surveillance and propaganda campaigns targeting foreign audiences spill back into the US because of the nature of the global media and information flows. The all-encompassing doctrine also blurs the boundaries between `normal' media spin and public affairs, on the one hand, and propaganda and covert media operations, on the other. The convergence of commercial media and the military and government in such operations is also yielding what some call the military—information—media—entertainment (MIME) complex. Lastly, the US military's heavy reliance on the Internet and other public communication networks means that cyberspace is being retooled to meet national security, surveillance, propaganda and cyberwarfare needs.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.043 | 0.008 |
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".