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Record W3109630555 · doi:10.1080/14747731.2020.1843842

Beyond land grabs: new insights on land struggles and global agrarian change

2020· article· en· W3109630555 on OpenAlexaff
Gustavo de L. T. Oliveira, Ben M. McKay, Juan Liu

Bibliographic record

VenueGlobalizations · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLand grabbingRestructuringAgrarian societyFinancializationAgribusinessConsolidation (business)Agricultural landLand reformPolitical scienceAgriculturePolitical economyEconomicsEconomyMarket economyGeographyFinance

Abstract

fetched live from OpenAlex

The conjunction of climate, food, and financial crises in the late 2000s triggered renewed interest in farmland and agribusiness investments around the world. This phenomenon became known as the ‘global land grab' and sparked debates among social movements, NGOs, academics, government and international development agencies worldwide. In this introduction, we critically analyse the ‘state of the literature' so far, and outline four areas that are moving the debate ‘beyond land grabs'. These include: (1) the role of contract farming and differentiation among farm workers in the consolidation of farmland; (2) the broader forms of dispossession and mechanisms of control and value grabbing beyond ‘classic’ land grabs for agricultural production; (3) discourses about, and responses to, Chinese agribusiness investments abroad; and (4) the relationship between financialization and land grabbing. Ultimately, we propose new directions to deepen and even transform the research agenda on land struggles and agroindustrial restructuring around the world.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0030.024
Scholarly communication0.0070.012
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.217
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations85
Published2020
Admission routes1
Has abstractyes

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