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Record W4415564321 · doi:10.1177/22779760251385308

Analysis of Changes in Extent and Composition of Land Tenancy in India: Exploration in Technology Adoption and Agricultural Profitability

2025· article· en· W4415564321 on OpenAlexaff
Mrityunjay Pandey, Nisha Patel, R. Vijay

Bibliographic record

VenueAgrarian South Journal of Political Economy A triannual Journal of Agrarian South Network and CARES · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsLeasehold estateProfitability indexProductivityAgricultureLivelihoodGreen RevolutionAgricultural land

Abstract

fetched live from OpenAlex

This article analyzes the evolving trends in tenancy contracts in India. Using official statistical data, the study observes a U-shaped pattern in the proportion of land leased and the share of cultivators engaged in tenancy over time. This declined until 1991–1992 and was followed by a considerable increase since 2002–2003. Notably, in the 1970s, semi-medium cultivators were the predominant tenant class. However, in the revival phase, landless and near-landless households emerged as the principal demanders for land under the tenancy. The article argues that in the 1970s, the green revolution and the changes in public policy related to agriculture caused an increase in productivity and profitability and the introduction of markets for many factors and output which were previously nontraded, all of which induced a decline in the extent of tenancy. In the subsequent phase, as the impact of new technology tapered out and state support declined, the rising cost of cultivation and reduced returns created disincentives for landowners to cultivate, giving rise to absenteeism and an employment and livelihood crisis and leading to the revival of tenancy and the emergence of labor-supplying households as the primary tenant group.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAgrarian South Journal of Political Economy A triannual Journal of Agrarian South Network and CARESSame topicLand Rights and ReformsFrench-language works237,207