Bibliographic record
Abstract
The concept of a public body deluded into believing whatever its leadersassert as truth might seem to recall Marxist theories of media and society. But this is an element of the reality painted by Paul Rutherford in hisWeapons of Mass Persuasion: Marketing the War against Iraq, in which heexamines Washington’s promotion of the war and its effectiveness in winningpublic support despite misinformation.Public opinion has been key to maintaining support for the war and thetremendous amount of money that it continues to pull out of the Americaneconomy. Rutherford investigates the marketing strategy, illustrates itseffects, and explores the significance of the experiment. His analysis providesan insightful look into how Washington was able to convince theAmerican people of the false threat of “weapons of mass destruction” andraises important questions about what the Bush administration’s “persuasion”experiment means for American democracy.The author dedicates the first three chapters to analyzing how the“weapons of mass persuasion” were deployed. However, the heart of hisstudy lies in the effects of those “weapons” on individuals and society. Hisresearch is centered in Canada and draws from its government and press.This makes it difficult to discern who is the focus of his analysis – is itCanadians, Americans, the Middle East, or the world at large? ...
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".