<i>Cultures in Conflict: The American Civil War,</i> by Steven E. Wood-worth
Bibliographic record
Abstract
Cultures in Conflict: The American Civil War, by Steven E. Woodworth. Westport, Connecticut, Greenwood Press, 2000. xx, 220 pp. $45.00 U.S. Steven E. Woodworth notes that concept of Culture Wars so aptly used by presidential candidate Patrick Buchanan at 1992 Republican National Convention, was neither new nor unique 1990s. According Woodworth, profoundly deep divisions that drive people to drastic action and fundamental change are always at least partly (p. xi). Citing American Civil War as one prominent example, Woodworth proposes help us understand cultural currents that caused and shaped that conflict through writings of actual participants and eye-witnesses. Following a three-page preface outlining his intent and methodology, Woodworth divides his book into three sections. Part I includes Key Events ... 1860-1865, an Overview chapter of war, and a chapter outlining Northern and Southern Ways of Life over two centuries. Part II contains four chapters of documents covering war years. A concluding part III considers Ideas Exploration, identifying links between various themes and specific documents, inferring its use discussion or research papers. The organization and approach thus suggests a book aimed at a student and non-specialist audience. The price ($45.00 U.S.) and book's structure may limit those uses. The documents include some thirty excerpts from letters, diaries and memoirs show mundane daily experiences of ordinary people (soldiers, nurses, teachers, a plantation mistress, farmers) both sides of conflict. Woodworth's sources are often imaginative. Wartime Southern culture is shown by Mary Todd Lincoln's half-sister in Kentucky, a family of Arkansas Unionists, Harriet Beecher Stowe's Georgian cousin, Braxton Bragg's wife, and a Union officer's wife in Nashville. More traditional civilian and soldier correspondence discuss Northern rural and small town communities with Wisconsin, New York, Pennsylvania, and Indiana heavily represented. Larger cities and eastern seaboard receive proportionately less attention. This fair representation is intended demonstrate intersection of military and civilian life and offer modern readers a chance know those who participated in war on a personal basis. Woodworth admits limits of this approach; illiterate persons, which includes most slaves are not included for obvious reasons and can only be represented in the accounts of others (p. xii). Surprisingly a book apparently aimed at students, he never explains why such non-traditional sources as slave narratives, songs, and oral tradition are excluded. …
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.012 |
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".