Bibliographic record
Abstract
The Civil War Experience Americans will mark the Civil War's sesquicentennial in a few years, but the subject of wartime atrocities is a relatively new field of study.Recent books, such as Black Flag over Dixie: Racial Atrocities and Reprisals in the Civil War, edited by Gregory Urwin (2004) and John Cimprich's Fort Pillow, a Civil War Massacre, and Public Memory (2005) examine wartime massacres and how Americans have remembered them.George S. Burkhardt, a former newspaper editor and journalist, apparently spent twenty years examining wartime atrocities, and his time was not misspent.Anyone examining the subject of no quarter during the Civil War should consult his study.Prolonged wars produce atrocities, and the Civil War was no different.But Burkhardt believes that such incidents were not isolated ones: they comprised part of a disturbing pattern of behavior.He takes a chronological approach to his subject, examining battles from the June 1863 fighting at Milliken's Bend, Louisiana, where African American troops took part in Grant's Vicksburg campaign to the fighting at Mobile and Selma in 1865.In his chapters, the author examines the war's most infamous massacre, the one Nathan Bedford Forrest's men committed at Fort Pillow, Tennessee; perhaps the worst massacre of any kind during the warùthe killing of African Americans at Plymouth, North Carolina; and the worst battlefield massacre, which occurred at the July 1864 Crater battle.Some of the battles Burkhardt describes are well-known to historians, others, such as the fighting at Olustee, Florida, in February 1864, and Fort Blakely, Alabama, in April 1865, are less famous.The battle at Fort Blakely, one Confederate wrote, resulted in the Yankee Fort Pillow (239), a Union victory that gave African Americans the chance to show no mercy toward 1 Woodward: Confederate Rage, Yankee Wrath: No Quarter in the Civil War
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.028 | 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".