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Record W2760204673 · doi:10.32396/usurj.v4i1.219

The Failures of Neoliberal Food Security and the Food Sovereignty Alternative

2017· article· en· W2760204673 on OpenAlexaffvenue
Laura Dawn Friesen

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFood securityFood sovereigntyFood systemsNeoliberalism (international relations)Context (archaeology)SovereigntyPolitical scienceIdeologyPolitical economySociologyDevelopment economicsEconomicsEconomic growthPoliticsAgricultureLawGeography

Abstract

fetched live from OpenAlex

Nearly one billion people suffer from hunger worldwide. This issue has been a central concern for the international community, with national governments, non-governmental organizations, and international organizations seeking solutions. The dominant response to the issue of hunger has largely centered around the concept of food security which emerged within a context dominated by neoliberal ideology. This Neoliberal Food Security approach has focused on expanding global food production and incorporating farmers into global food markets. Yet, despite decades of programs and initiatives, hunger remains a daunting problem. Food Sovereignty has been offered as an alternative approach, challenging the assumptions and conceptualizations which underpin Neoliberal Food Security and seeking to alter thestructures and unequal power relations inherent in the current global food system. This paper asserts that because Neoliberal Food Security fails to challenge the structures and inequalities which perpetuate hunger, it is an insufficient method for addressing the problem. In contrast, Food Sovereignty objects to the theories and practices of neoliberalism, thereby offering a radical alternative approach.

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)0.012
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.990
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.065
Scholarly communication0.0090.009
Open science0.0010.010
Research integrity0.0030.008
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 head0.029
GPT teacher head0.245
Teacher spread0.216 · 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
GenreOther

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

Citations6
Published2017
Admission routes2
Has abstractyes

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Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207