Brian Steel Wills. Inglorious Passages: Noncombat Deaths in the American Civil War.
Bibliographic record
Abstract
In Inglorious Passages: Noncombat Deaths in the American Civil War, Brian Steel Wills argues that while not every death during the American Civil War was the result of so-called “honorable circumstances,” all mattered deeply to those who mourned their passing. For every man who died, whether ingloriously or not, to “their friends and their loved ones the loss was real. Their lives mattered” (300). New estimates of the Civil War death toll are that as many as 750,000 men died as a result of the war. Wills refines this to show that as many as 400,000 of these deaths were not directly related to the battlefield but were the result of disease, extreme weather, suicides, executions, homicides, “acts of God,” artillery accidents, drownings, “cantankerous army mules” (125), friendly and not so friendly fire, and railway accidents. The book is well researched and the author has found numerous interesting cases of noncombat deaths. He dives deep into this novel topical crevice to explore the range of deaths, but perhaps because they were so many and various, he moves somewhat superficially over the broader significance of their meaning. Death was of course the most widely shared event of the war, and Drew Gilpin Faust’s seminal study This Republic of Suffering: Death and Suffering in the American Civil War (2008) demonstrates the ways in which the dead body assumed a new symbolic value for society, thus transforming ideas about death. The so-called “good death” that was expected of men was long part of respectable middle-class behavior and acceptance of death as God’s will. But Wills does not probe the larger meaning of noncombat-related deaths—what those without the aura of battlefield glory but concurrent with it signified to Americans. Legislation in 1867 attempted to locate and bury Union soldiers in a national cemetery, but were noncombatants similarly honored? Death was seen as a spiritual transition, but what was the moral lesson of the many who died from alcohol? The warrior dead allowed the living to reimagine a national community for the reunited states, but what of these “inglorious” deaths?
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".