Bibliographic record
Abstract
Martha C. Nussbaum’s The Tenderness of Silent Minds makes an important contribution to our understanding of the relationship between the arts and society. Through an extended analysis of Benjamin Britten’s War Requiem, Nussbaum argues that art has the power to “transform the consciousness of the makers of war in our world, producing real thought about future wars and an opening to a stable peace” (p. 3). This is, unfortunately, as needed in 2025 as it was in 1961, when Britten finished his Requiem. Nussbaum shows how art can help audiences (a) confront the consequences of war on the bodies of soldiers as well as those who toil at home; (b) expose the futility of retributive anger; and (c) encourage us to approach even our enemies with a spirit of love. She uses the War Requiem as her central example, despite its “tacit assumption” (in using Wilfred Owen’s World War I poetry in a work about World War II) that the two world wars were “equally, and similarly, pointless” as well as its creator’s “grave ethical error” in failing to recognize the latter as a just war (pp. 4–5). In refusing even supportive national service work, she describes Britten and his partner Peter Pears as “free riders on the courage and suffering of others” (p. 113). Nussbaum argues that Britten’s War Requiem survives these failings because the insights it offers are, to a large extent, compatible with the belief that the use of physical force is justified in the defense of self or others.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.056 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.021 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".