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Record W2087549382 · doi:10.3098/ah.2009.83.3.352

An Unremembered Diversity: Mixed Husbandry and the American Grasslands

2009· article· en· W2087549382 on OpenAlexaff
Kenneth M. Sylvester, Geoff Cunfer

Bibliographic record

VenueAgricultural History · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Literature and Culture
Canadian institutionsUniversity of Saskatchewan
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsMonocultureGeographyAnimal husbandryAgricultureCrop diversityDiversity (politics)BiodiversityAgroforestryCropAgricultural economicsAgronomyPolitical scienceArchaeologyEcologyForestryEconomicsBiology

Abstract

fetched live from OpenAlex

The Green Revolution of the 1960s brought about a dramatic rise in global crop yields. But, as most observers acknowledge, this has come at a considerable cost to biodiversity. Plant breeding, synthetic fertilizers, and mechanization steadily narrowed the number of crop varieties commercially available to farmers and promoted fencerow-to-fencerow monocultures. Many historians trace the origins of this style of industrialized agriculture to the last great plow-up of the Great Plains in the 1920s. In the literature, farms in the plains are often described metaphorically as wheat factories, degrading successive landscapes. While in many ways these farms were a departure from earlier forms of husbandry in the American experience, monocultures were quite rare during the early transformation of the plains. Analysis of a large representative sample, based on manuscript agricultural censuses and involving twenty-five townships across the state of Kansas, demonstrates that diverse production reached even the most challenging of plains landscapes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.014
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.010
GPT teacher head0.175
Teacher spread0.164 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations9
Published2009
Admission routes1
Has abstractyes

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