THIRD PRIZE: Coherence in Crisis: Groupthink, the news media, and the Iraq War
Bibliographic record
Abstract
This paper provides an analysis of the role of the news media on American military strategy in the 2003 Iraq War. It argues that American policy makers, displaying the symptoms of Irving Janis’ theory groupthink, had more autonomy in decision-making because of barriers setup by the group to ignore external sources of criticism and taking action to limit doubts within the group on the strategy being employed. As a result, the US executive had more freedom of action than is frequently perceived by scholars supporting the notion that news media organizations possess extensive agenda-setting power, commonly known as the “CNN effect.” The arguments of scholars supporting the agenda-setting power of media organizations are discussed and evaluated to determine if US military strategy was affected by the largely negative media presence in this conflict. This paper is unique because it shifts focus away from the field of foreign policy, and specifically the decision making process surrounding engagement and extraction from war zones, and instead focuses the news media’s role in influencing strategic direction of a war. It concludes that the negative tone of the news media did not have a significant effect on military strategy due to strong cohesiveness of American elites throughout the conflict, and the inability of news makers to force any noticeable changes to military activities.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".