Mourning in the Age of Terror: Revisiting Don DeLillo’s Elusive 9/11 Novel <i>Falling Man</i>
Bibliographic record
Abstract
This article revisits Don DeLillo’s 2007 novel Falling Man—generally considered a minor work in the author’s oeuvre—in the wider contexts of the American novel after 11 September, contemporary discourses around terrorism, the “War on Terror,” and recent currents of global ethnonationalism. It is organized around an iconic photograph in modern American history, one of an anonymous man falling from the North Tower of the World Trade Center shortly before its collapse, as well as around DeLillo’s difficult novel named after this same photo. These works are primarily interpreted herein through Emmanuel Levinas’s analysis of images as symbolic substitutions and Sigmund Freud’s “Mourning and Melancholia,” which I use to ask critical questions about Falling Man’s expression of the societal shock represented by 9/11 and of private and public mourning in response to terrorism, as well as about what it means to be unable to mourn altogether.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.042 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".