Arise! Global Radicalism in the Era of the Mexican Revolution, By Christina Heatherton
Bibliographic record
Abstract
Christina Heatherton’s book is an inspiring investigation into convergences in radical politics in the first half of the twentieth century. What some have dismissed as coincidence, Heatherton theorizes as spaces where radicalism flourished, demonstrating that although it can be hard to pin down the transfer of revolutionary ideas, scholars must do so to attend to the alternative narratives and historical agency they uncover. This is a bold and exciting study that demonstrates the promise of American studies approaches for understanding the hemisphere and beyond. In each of the six chapters, Heatherton examines a different “convergence space,” which she defines as “contradictory socio-spatial sites wherein people from different backgrounds and different radical traditions have been forced together and have subsequently produced new articulations of struggle” (p. 18). The first, which provides the nineteenth-century context to the subsequent chapters, examines the convergence of revolutionary thought in 1848 with the loss of Mexico’s northern territory to the United States and the coming of the U.S. Civil War. She demonstrates, through an analysis of the short-lived Mexican port of Bagdad, how the emergence of global capitalism was central to the rise of the U.S. hegemonic order in the hemisphere. In the second, she analyses the internationalism of Shinsei “Paul” Kōchi, Manabendra Nath Roy, and John Reed. In their writings each reconciles the Russian Revolution and the Mexican Revolution through their firsthand experiences, to articulate new ideas about the mechanics of imperialism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.010 |
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".