Lynching in the West: 1850-1935. By Ken Gonzales-Day. (Durham: Duke University Press, 2006. xiv, 299 pp. Cloth, $79.95, ISBN 978-0-8223-3781-2. Paper, $22.95, ISBN 978-0-8223-3794-2.)
Bibliographic record
Abstract
Ken Gonzales-Day's deeply researched book highlights the extensive lynching violence that plagued California from the mid-nineteenth century through the first decades of the twentieth century. Gonzales-Day documents 352 victims of mob killing in the Golden State from 1850 through 1936, with 132 of those victims (38 percent) identified as Mexican or Latin American. As with the recent work of historians such as William D. Carrigan and Clive Webb, Gonzales-Day's analysis stresses the wide-scale collective violence of Anglos against Hispanics. Like Carrigan and Webb (whose findings he could do more to acknowledge), Gonzales-Day argues that the widespread lynching of Hispanics should lead historians to rethink histories of the West that have tended to ignore the racial dimensions of vigilante violence in favor of a narrative of “frontier justice.” Also like Carrigan and Webb, Gonzales-Day urges historians of lynching to broaden interpretations that have tended to focus on the lynching of African Americans in the South.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".