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Record W2093796527 · doi:10.1353/rah.0.0142

Reexamining America's Agricultural Development

2009· article· en· W2093796527 on OpenAlexaboutno aff
Brian Q. Cannon

Bibliographic record

VenueReviews in American History · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureGovernment (linguistics)Index (typography)AcreLivestockEconomic historyAgricultural economicsPolitical scienceEconomicsHistoryAgricultural scienceGeographyArchaeologyForestryPhilosophy

Abstract

fetched live from OpenAlex

Reexamining America's Agricultural Development Brian Q. Cannon (bio) Alan L. Olmstead and Paul W. Rhode. Creating Abundance: Biological Innovation and American Agricultural Development. New York: Cambridge University Press, 2008. xii + 467 pp. Figures, tables, maps, photographs, notes, bibliography, index. $80.00 (cloth); $23.99 (paper). In this important revisionist book, Alan L. Olmstead, Distinguished Professor of Economics at the University of California, Davis, and Paul W. Rhode, McClelland Professor of Economics at the University of Arizona, demonstrate conclusively that biological innovation was a key factor in sustaining production on American farms in the two centuries prior to 1940. They argue that "American farmers and their allies in universities, government, and industry were keenly interested in biological innovation, and reaped considerable returns from those investments" (p. 387). In writing about the ways American agriculture developed up to the 1930s, generations of economists and economic historians including Willard Cochrane, D. Gale Johnson, William Parker, Judith Klein, Jeremy Atack, Fred Bateman, and Peter McClelland have concentrated heavily upon labor-saving technological innovations such as the cotton gin and the McCormick reaper. Because yields per acre changed little between 1800 and the 1930s, when hybrid corn was developed, economic historians have assumed that new varieties of crops and livestock exerted little impact upon agricultural output in those years. Farmers lacked the motivation to experiment with new crops, they have reasoned, until land became expensive relative to labor. Thus, in places like Japan and Korea, where land was scarce but labor was abundant, farmers invested in biological technology that would improve yields per acre. But in Australia, Canada, and the United States—where land abounded and labor was scarce—farmers invested primarily in machinery so that they could cultivate more land. Scholars whose primary training is in history rather than economics have not entirely ignored biological improvements in their accounts of American agriculture prior to 1940. James C. Malin, for instance, thoroughly traced the process leading to widespread adoption of new varieties of wheat on the [End Page 591] Central Plains in Winter Wheat in the Golden Belt of Kansas. But historians, like economists, have often emphasized technology over biological innovation in writing about agriculture prior to the 1930s. For instance, in his survey American Agriculture: A Brief History, R. Douglas Hurt devotes a little over three pages to the introduction of new seeds and breeds in the antebellum era, but he takes thirteen pages to discuss technological developments. Similarly, in his account of agriculture in the Gilded Age, Hurt describes new machinery and its impact in eight pages, followed by a one-half page overview of scientific discoveries that enabled farmers to combat plant and animal disease and understand soil fertility. In his survey Born in the Country: A History of Rural America, David B. Danbom attributes the rise in cotton production in the antebellum era to high consumer demand and improved technology in the form of the cotton gin; he neglects the connection between new varieties of cotton and increased production. In later chapters, though, Danbom more evenly balances technological and biological innovation. He describes important machinery, including the McCormick reaper and the tractor; but he also highlights the work of the U.S. Department of Agriculture, land-grant universities, and agricultural experiment stations in gathering cultivars from across the globe, developing new varieties, and disseminating information. While they acknowledge that technology was important, Olmstead and Rhode argue in this revisionist study that biological adaptation was just as significant. Farm output would have fallen precipitously between 1800 and 1930 if farmers had not discovered and planted new varieties of crops that were resistant to vexatious diseases and pests. They posit that nearly the entire grape crop, along with 50 to 80 percent of the wheat, cotton, oranges and other fruit grown in the United States in 1940, would have been lost to disease and insect pests if farmers had not shifted to new varieties of crops between 1830 and 1940. Olmstead and Rhode arrived at these estimates using historical records of crop losses and "the testimony of plant scientists, field trials, and natural experiments" (p. 388). These dire speculative scenarios are grounded sufficiently enough in historical evidence of actual crop losses to...

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.017
GPT teacher head0.216
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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