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Record W3007816092 · doi:10.1080/14747731.2020.1730050

The global food system, agro-industrialization and governance: alternative conceptions for sub-Saharan Africa

2020· article· en· W3007816092 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 Guelph
Fundersnot available
KeywordsCommodificationFood securityIndustrialisationGlobalizationCorporate governanceLivelihoodEconomicsCapitalismAgriculturePolitical economyPolitical scienceMarket economy

Abstract

fetched live from OpenAlex

Global food security challenges give rise to contentious debates. Conventional approaches to agricultural development call for capital-intensive industrial-scale farming to increase global productivity. Sub-Saharan Africa is the main target for agro-industrial farmland investments. Critical scholars oppose these trends in the region, arguing that the large-scale farming model causes a devastating loss of land resources and harms rural livelihoods. Critical development scholars and critical globalization scholars generally intersect in their candid rejection of global capitalism and the commodification of agri-food resources. This paper adds to existing critiques by advancing a governance approach. In reviewing case study evidence from eight countries, it highlights the crucial role of governments, who ultimately wield sovereign authority to regulate the agricultural sector. This analysis represents a fusion of critical development studies and critical globalization studies. Rather than rejecting the global capitalist system, it sheds light on the need for effective regulation and identifies key actors and policy areas.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.625

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 studies0.0010.000
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 head0.034
GPT teacher head0.223
Teacher spread0.189 · 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