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Record W2899947547 · doi:10.1017/s1742170518000522

From farming to food systems: the evolution of US agricultural production and policy into the 21st century

2018· article· en· W2899947547 on OpenAlexfundno aff
Carolyn Dimitri, Anne Effland

Bibliographic record

VenueRenewable Agriculture and Food Systems · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersAdvanced Research Projects AgencyNational Institutes of HealthYork UniversityU.S. Department of Agriculture
KeywordsAgricultureFood systemsAgricultural economicsOrganic farmingAgricultural policyMainstreamBusinessFood processingProduction (economics)Conservation agricultureConsolidation (business)Agricultural productivityNatural resource economicsFood securityEconomicsGeographyPolitical science

Abstract

fetched live from OpenAlex

Abstract Nearly two decades into the 21st century, we revisit the topic of changes in the US agricultural system. We focus on trends in structure, technology and policy, and on the increasing influence of consumer preferences on this system, particularly for organic agriculture and local and regional foods. We examine technological innovations in the 21st century, including biotechnology, precision agriculture and indoor farming. Within overall trends toward consolidation, we identify an increasing number of vegetable farms and greenhouse operations, accompanied by a decrease in average size of those operations. We note the shift away from price support toward greater reliance on risk management in farm policy, and also track the impact of food movement trends on recent farm bills. While farm bill policies continue to focus on conventional field crop agriculture, some trends—expanded crop insurance, conservation program support and spending on federal data collection, research and community-based grants, for example—have begun to incorporate the growing movement toward organic, local and regional food systems into the mainstream of US agricultural production and policy.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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 teacher head, not a consensus.

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

Citations28
Published2018
Admission routes1
Has abstractyes

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