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Record W2246685147

Tobacco Grower Livelihoods During Agricultural Restructuring

2008· article· en· W2246685147 on OpenAlexvenueno aff
Verdie A. Craig

Bibliographic record

VenueJournal of rural and community development · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringLivelihoodDiversification (marketing strategy)Cultivation of tobaccoAgricultureBusinessLegislationAgricultural economicsEconomic growthPolitical scienceEconomicsGeographyFinance
DOInot available

Abstract

fetched live from OpenAlex

In the summer of 2002, Kentucky tobacco farmers had undergone production cuts of more than sixty percent and federal legislation had been proposed for a tobacco buyout. Semi-structured interviews were conducted with 58 Kentucky farmers to learn how tobacco growers were responding to production cuts and/or engaging with tobacco restructuring more broadly. While tobacco restructuring could have been the catalyst toward a more diversified and sustainable agriculture, farm diversification had not taken place for the majority of Kentucky tobacco farmers. While farm diversification was fairly scarce, income diversification in response to tobacco restructuring was widespread. Outside of (mostly European) studies of pluriactivity, studies of livelihood and livelihood transition have traditionally focused on less-developed countries. In addition to the utilitarian lessons of this research, this study extends understanding of farmer livelihood transition in a developed country (the United States).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.001
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 head0.032
GPT teacher head0.224
Teacher spread0.193 · 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 designObservational
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

Citations4
Published2008
Admission routes1
Has abstractyes

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