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Record W3031982543 · doi:10.1080/03056244.2019.1688486

The social life of wheat and grapes: domestic land-grabbing as accumulation by dispossession in rural Egypt

2019· article· en· W3031982543 on OpenAlexfundno aff
Yasmine Moataz Ahmed

Bibliographic record

VenueReview of African Political Economy · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersHorizon 2020Leibniz-GemeinschaftCentre National de la Recherche ScientifiqueEuropean Research CouncilInternational Development Research Centre
KeywordsLand grabbingPolitical scienceLand reformDevelopment economicsGeographyEconomicsAgriculture

Abstract

fetched live from OpenAlex

ABSTRACT In the last three decades, Egypt’s rural population has experienced different types of struggle over land as a result of neoliberal land reforms, which have favoured landowners and marginalised tenants’ interests. While the literature highlighted the negative effects on the tenants, little attention was given to what landlords did with the land after the reforms. Drawing on fieldwork conducted between 2011 and 2013 in five Egyptian villages, the article addresses this lacuna by investigating tenants’ understanding of land-use change. Using a revised conceptualisation of Marx’s metabolic rift, the article shows that evicted tenants understand this shift as part of a domestic land grab that disrupted the ecological system. The article therefore conceptualises land dispossession and domestic land grabs as mutually reinforcing processes and draws particular attention to the sensorial dimensions associated with domestic land grab, in addition to the political and economic dimensions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.270
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2019
Admission routes1
Has abstractyes

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