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Record W2474693477 · doi:10.5539/ass.v12n8p184

Collective and Organic Farming in Tamil Nadu: Women’s Participation, Empowerment and Food Sovereignty

2016· article· en· W2474693477 on OpenAlexvenueno aff
Dhruv Pande, Munmun Jha

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsFood sovereigntyEmpowermentTamilSovereigntyEconomic growthAgricultureCasteOppressionPoliticsState (computer science)Political scienceSociologyPolitical economyFood securityEconomicsGeographyLaw

Abstract

fetched live from OpenAlex

<p>The aim of this paper is to explore the notion of women’s participation, empowerment and food sovereignty among the marginalized women farmers in the state of Tamil Nadu in India. The women farmers who belong largely to the so-called lower castes have been marginalized due to the persistent presence of the patriarchal structure and the continued oppression and discrimination in a caste-ridden society. This is supported and supplemented by the policies and politics of globalization through the state apparatus. This research, based on the fieldwork method, highlights the hitherto undermined role of women farmers in the wake of their efforts at establishing enhanced and sustainable socio-economic relations in connection with the local agricultural land which accounts for their economic and social independence and sovereignty, especially food sovereignty. The process marking this transformation includes collective and organic farming based on millets leading to the creation of an inherent and integral food sovereignty vis-a-vis the increasing usurpation of agricultural land through the nexus of the state government and private companies. The paper also analyzes the issue of land ownership, litigation cases involving women, and the role of community organizations which impel the hitherto marginalized women towards self-sustainable, self-sufficient and self-governed environment in rural agricultural economy.</p>

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.418

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 head0.011
GPT teacher head0.218
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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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