Dependent Harvests: Grain Production on the American and Canadian Plains and the Double Dependency with Mexico, 1880–1950
Bibliographic record
Abstract
Abstract For nearly sixty years, roughly 1880 to 1950, before the affordability and wide-spread use of combines, grain production in the American and Canadian Great Plains was dependent on harvesting with binders. Binders cut the grain stalks and then tied them into bundles with twine that farmhands later would gather into shocks to await threshing. The majority of the twine used was made from fiber from agave plants (sisal and henequen) from Mexico’s Yucatan Peninsula. The dependency on this Mexican commodity is illustrated by the fact that for the first two decades of the twentieth century, the United States and Canada consumed an estimated 230,000 tons of the fiber a year for the production of binder twine. Thus, a double agricultural dependency developed between these regions that this essay seeks to explore. Along with this international dependency, corporate, social, and labor issues are integral aspects of the grain/twine story. International Harvester of Chicago came to dominate the twine industry in the United States, but faced stiff competition from American and Canadian penitentiaries that developed their own twine mills using low-wage inmate labor. And in Mexico, wealthy henequen estate owners enslaved Yaqui Indians from Sonora to work in their fields in the Yucatan. "Dependent Harvests" seeks to introduce these themes and to cast them into their proper transnational and agricultural history perspectives.
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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 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".