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Record W2162801018 · doi:10.1525/aa.2006.108.2.363

Why Grow Cash Crops? Subsistence Farming and Crop Commercialization in the Kolli Hills, South India

2006· article· en· W2162801018 on OpenAlexaff
Elizabeth Finnis

Bibliographic record

VenueAmerican Anthropologist · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSubsistence agricultureCash cropCommercializationCashAgricultureContext (archaeology)Agency (philosophy)BusinessEconomic growthAgricultural economicsMarketingGeographyEconomicsSociologySocial scienceFinance

Abstract

fetched live from OpenAlex

In this article, I provide an analysis of local decision making surrounding crop commercialization in the Kolli Hills, South India. I argue that in the context of changes in the physical environment, cultivating tapioca (cassava) as a cash crop is a conscious decision made by small farmers based on their perceptions of environmental insecurity. Farmers understand market integration as key to coping with external, uncontrollable changes and to fulfilling household and community aspirations. Decisions to cultivate tapioca have contributed to aspects of community development and increasing political agency on the part of villagers.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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

Citations34
Published2006
Admission routes1
Has abstractyes

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