At War with Metaphor: Media, Propaganda, and Racism in the War on Terror
Bibliographic record
Abstract
* At with Metaphor: Media, Propaganda, and Racism in the on Terror. Erin Steuter and Deborah Wills. Lanham, MD: Lexington Books, 2008. 244 pp. $70 hbk. $29.95 pbk. $70 E-book. Erin Steuter and Deborah Wills, who teach sociology and English at Canada's Mount Allison University, are commited to raising the level of public understanding about the role that play in bringing people into and through a seemingly endless string of wars. Although this book is focused primarily on U.S. constructions of the so-called War on Terror, its emphasis on the role that metaphor plays in the strategic of countless enemies helps to establish the historical roots of this discursive practice. Although the authors acknowledge the important contribution to our understanding of various that have been provided by the alternative media, this book is primarily a critical assessment of the complicity with which the mainstream media support their government's use of propaganda as a strategic resource. The book begins with an accessible introduction to the nature, role, and routine use of metaphor within communications in general, and within mass in particular. Because of its concern with the call to war and the metaphoric construction of the enemy, most of the book's examples have been chosen to illustrate the use of readily interpreted images of the Other as subhuman, dangerous, and worthy of little short of annihilation. In one chapter, this metaphoric othering is associated with Orientalism as an especially extreme form of construction that frames the other as not only different, but essentially the opposite of all that we value in ourselves. The dehumanization of the enemy is accomplished routinely in the nexus of racism and genocide, and it is in this context that Steuter and Wills provide historical examples of the use of metaphor to justify the most extreme treatment of slaves, Jews, Rwandans, and Asian enemies of wars past. The second of three sections in the book is focused on three contemporary case studies that identify some of the common threads that tie the process of dehumanization together. The first, and perhaps most familiar, discursive strategy is the use of animals and disease, and the implied links between them to invite us to accept extermination as an appropriate military response. The strategic use of images and labels of particular animals is quite common in part because of the deeply engrained aversive responses that most of us have to rats and other vermin. Similarly shared impressions of the character of individual animals like weasels help to reinforce the impressions of the enemy as treacherous, sneaky, and cowardly. One chapter is devoted to the use of these constructions of the enemy as vermin, and their actions as infestation, in order to justify eradication through extermination. …
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".