Between Rhetoric and Propaganda: A Case Study of Appeals to Pathos in Iraq War Justification
Bibliographic record
Abstract
This MRP explores the ethical dilemma inherent in the use of emotional appeals in political speeches. Taking a historical approach to the question of how ethics and emotion have played out in rhetorical theory and propaganda studies, I examine how political speakers use rhetorical appeals to pathos in order to gain support for controversial policies. I question where the “line” between legitimate rhetorical appeals to pathos and illegitimate, emotionally manipulative propaganda lies, and ask: do appeals to emotion constitute propaganda? What is the difference between a legitimate appeal to emotion and propaganda? What constitutes a “legitimate” appeal to emotion in political speech? To answer this, I analyze three speeches made by Western political leaders justifying America’s decision to invade Iraq in 2003. My analysis distinguishes different kinds of appeals to pathos, or emotion, within my data set and weighs each speaker’s use of “legitimate” appeals to pathos against emotional appeals that are classified as “propaganda,” according to Elspeth Tilley’s Propaganda Index (2005). My findings show that a large percentage of appeals to pathos in each speech analyzed meet the requirements for propaganda as defined by Tilley. Eighty-one percent of appeals to pathos in George W. Bush’s “Message to Saddam” constitute propaganda; sixty-eight percent of appeals to pathos in Tony Blair’s Speech to the British House of Commons constitute propaganda; and seventy-three percent of appeals to pathos in Stephen Harper’s Speech to the Canadian House of Commons are considered propaganda as defined by Tilley. My findings showcase the ambiguity of “ethical” communication in political contexts, and underline the importance of critical audience engagement in political processes.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".