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Diversification in Indian Agriculture toward High‐Value Crops: The Role of Small Farmers

2012· article· en· W1996412348 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsDiversification (marketing strategy)EconomicsAgricultureAgricultural scienceGeographyBusinessBiology

Abstract

fetched live from OpenAlex

Diversification by small farmers toward high‐value crops (fruits and vegetables [F & V]) that can raise farm incomes significantly has always been in question because of several reasons such as diseconomies of scale and lack of access to inputs such as capital and information. We present evidence that in India diversification toward high‐value crops exhibits a pro‐smallholder (rather than anti‐smallholder) bias. The smallholders however play a proportionally larger role in vegetables than in fruits cultivation. These patterns are consistent with simple comparative advantage‐based production choices. Even with small landholdings if labor endowments are high, such farmers diversify toward F & V. Though fruits cultivation is also labor intensive relative to cereals, it is less so relative to vegetables. Greater capital intensity implies a comparatively important role of credit in fruits. The results are robust to several tests on specification including those related to self‐selection. Chez les petits exploitants agricoles, la diversification en faveur de cultures à valeur élevée (fruits et légumes) permettant d’accroître considérablement le revenu agricole a toujours été remise en question pour diverses raisons, notamment les déséconomies d’échelle et le manque d’accès aux intrants comme le capital et l’information. Dans le présent article, nous montrons qu’en Inde, la diversification en faveur de cultures à valeur élevée semble plutôt favorable que défavorable aux petits exploitants agricoles. Toutefois, les petits exploitants sont proportionnellement plus présents dans la culture maraîchère que dans la culture fruitière. Ces observations concordent avec les choix d’une production fondée sur les avantages comparatifs. Même dans le cas des petites exploitations, lorsque les besoins de main‐d’œuvre sont élevés, elles se tournent vers les cultures fruitière et maraîchère. Bien que la culture fruitière soit une activitéà forte intensité de main‐d’œuvre comparativement à la culture céréalière, elle l’est moins que la culture maraîchère. L’intensité de capital élevée de la culture fruitière signifie que le crédit joue aussi un rôle important. Les résultats de plusieurs tests de spécification sont robustes, y compris ceux liés à l’auto‐sélection.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.154
Teacher spread0.132 · 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