Bibliographic record
Abstract
In his book, 9/11: The Culture of Commemoration, David Simpson recognizes the political work of violence, suggesting “[w]ar cannot easily survive the capacity to imagine oneself in the body of the other.”2 As Simpson infers, the notion of being embedded in the life of another poses significant challenges to the perpetuation of violent acts. In this paper, I offer a re-theorization of violence that takes up the metaphor of “organic shrapnel”, a phenomenon in which human flesh from a suicide bomber or victim is driven under the skin of a survivor. What organic shrapnel suggests is not only that the body is simultaneously permeable and weaponized; the image also constructs trauma as a relational and possibly ethical experience. Using the figure of organic shrapnel, I argue for a broader understanding of the term violence itself – one that addresses its unfolding in both space and time rather than as an absolute and single act. Working through several ways of re-theorizing violence with regard to hospitality, the body, its spatial and temporal threshold and the significance of the other, the paper asks: what might it mean to reconsider violence as a site of potential ethical formation and address rather than the foreclosure of relational bonds?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.066 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".