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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 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
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