Boodle over the Border: Embezzlement and the Crisis of International Mobility, 1880–1890
Bibliographic record
Abstract
Roughly 2,000 American fugitives fled to Canada in the 1880s—mostly clerks, cashiers, and bank tellers charged with embezzlement. This article argues that these “boodlers,” as they were popularly called, were symptomatic of a late-nineteenth-century crisis of mobility. Embezzlement was a function of new kinds of mobility: migration to cities, the rise of an upwardly mobile middle class, the fungibility of greenbacks, and the growth of international transportation networks. The boodlers were some of the earliest white-collar criminals. By focusing on their unexplored story, this article contributes to the growing literature that presents the clerk as an important figure in nineteenth-century labor history. Still, the boodlers also had a more unexpected impact on the evolution of the United States' international borders, both in the popular imagination and in actual surveillance and law enforcement techniques. Through the figure of the boodler, this article examines the links between the growth of capitalism and the development of the United States–Canada border in the late nineteenth century.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".