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Record W4411014663 · doi:10.3386/w33854

Internal Migration and the Spatial Reorganization of Agriculture

2025· report· en· W4411014663 on OpenAlexfundno aff
Raahil Madhok, Frederik Noack, Ahmed Mushfiq Mobarak, Olivier Deschênes

Bibliographic record

VenueNational Bureau of Economic Research · 2025
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
FundersCanada Research Chairs
KeywordsAgricultureInternal migrationEconomic geographyGeographyEconomicsArchaeologyEconomic growth

Abstract

fetched live from OpenAlex

This paper studies how agricultural production responds to the loss of agricultural labor during the process of urbanization and structural transformation.Using household microdata from India and exogenous variation in migration opportunities induced by urban income shocks, we show that agricultural households do not systematically replace lost labor with increased capital.Instead, they cultivate less land and lower their use of agricultural technology, reducing crop production.Resulting changes in land and crop prices induce non-migrant households to expand agricultural investments and production.In aggregate, market adaptation mitigates over three-fourths of the direct agricultural losses from urbanization.Spatial reorganization moves food production from land near urban areas toward more remote areas with lower emigration.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.109
GPT teacher head0.399
Teacher spread0.291 · 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 designNot applicable
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

Citations3
Published2025
Admission routes1
Has abstractyes

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