Bibliographic record
Abstract
This article addresses the relative silence of American intellectuals in the face of what can be termed the greatest act of terrorism ever committed by a nation-state, the bombing of Hiroshima and Nagasaki. I analyze this indifference by American intellectuals as partly due to their taming by a cultural apparatus that functions largely as a disimagination machine in conjunction with the neoliberal forces of commodification, privatization, and militarism. I argue that terror and violence are now addressed within a public pedagogy driven by a spectacle of violence that defines itself as entertainment but is actually a form of public pedagogy that thrives on an excess of representation and an attempt to produce a collective surrender to political cynicism and apocalyptic despair. In this instance, despair and cynicism, if not a retreat from any sense of moral responsibility, are deeply embedded in a mode of politics in which education is central to a flight from social responsibility and an embrace of modes of depoliticization. The article concludes by calling upon educators, intellectuals, artists and others to create the institutions, public spheres, and other sites necessary to develop a critical formative culture capable of reclaiming public memory while simultaneously producing critically engaged intellectuals and a vibrant democratic polity.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".