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Land Reform, Rural Social Relations and the Peasantry

2007· article· en· W2167501000 on OpenAlexaff
A. Haroon Akram‐Lodhi

Bibliographic record

VenueJournal of Agrarian Change · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsTrent University
Fundersnot available
KeywordsFood sovereigntyAgrarian reformLand reformSovereigntyAgrarian societyPolitical economyAgrarian systemVisionPower (physics)PoliticsPolitical scienceSociologyEconomicsEconomyFood securityLawAgricultureHistory

Abstract

fetched live from OpenAlex

A new book, Promised Land: Competing Visions of Agrarian Reform , edited by Peter Rosset, Raj Patel and Michael Courville is considered. This book, via both general analytical treatment and a series of case studies set in Latin America, Asia and Africa, offers a powerful critique of the World Bank's market‐led agrarian reform (MLAR) and provides an alternative model of agrarian reform, the ‘food sovereignty movement’, that has been articulated by La Via Campesina. Food sovereignty requires that priority be allocated to the domestic production of food and that a right to land be given to small farmers and their families. It is a vision of agrarian reform, with an emphasis on smallholder farming and the transformative power of rural social movements, that has truly emerged ‘from below’. The critique of MLAR is compelling. It is argued in this essay, however, that two crucial questions are abstracted from. The first is that of the vastly differing sets of social relations that exist (compare, say, socialist Cuba and capitalist Brazil) and their implications. It is not clear that food sovereignty can, in effect, offer a coherent political economy of an alternative global agrarianism. The second relates to the implicit assumption, found throughout the book, that the peasantry is a homogeneous, undifferentiated social group. This is manifestly not so, and what the existence of socially differentiated peasantries implies requires careful examination.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.221
Teacher spread0.196 · 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

Citations25
Published2007
Admission routes1
Has abstractyes

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