Leadership Styles and Policy Breakdown: Bush and Rumsfeld and the War in Iraq
Bibliographic record
Abstract
Drawing on European folktales, Isaiah Berlin once divided cognitive approaches between those who see problems like hedgehogs, focusing on one big thing, and foxes, who know many little things. Based on two dozen interviews with senior policy advisors and officials, Stephen Dyson applies this bifurcation to George W. Bush and Donald Rumsfeld, with Bush as the simplistic black and white hedgehog, and Rumsfeld as the complex and sometimes wily fox. Dyson's work privileges the study of individual leaders in the study of international politics and, contra realism, he argues that it is impossible to understand the war in Iraq without considering the personalities of the President and his Secretary of Defense. This study complements Dyson's earlier work on conflict and leaders, including Tony Blair, Margaret Thatcher, Adolf Hitler, and Saddam Hussein. The basic message of the book is repeated throughout, and most cogently articulated at the end: “George W. Bush's worldview was based upon clear-cut principles, instinctive, non-reflective decision making, a strong moralistic bent, and a propensity for risk-taking based upon a belief in the history-making potential of strong leadership… [In contrast] Rumsfeld saw the world as filled with nuance, complexity and contingency. He was obsessed with the unknowable, and deeply suspicious of grand doctrines or ambitious policy schemes” (p. 125).
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".