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Record W1910801685 · doi:10.15353/cfs-rcea.v2i2.103

Mapping the state of play on the global food landscape

2015· article· en· W1910801685 on OpenAlex
Jennifer A. Clapp (University of Waterloo), Annette Aurélie Desmarais, Matias E. Margulis

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.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of WaterlooUniversity of ManitobaPierre Elliott Trudeau FoundationUniversity of Northern British Columbia
KeywordsFood securityLand grabbingFood systemsPovertyFood sovereigntyAgricultureSustainabilityFood processingRight to foodBusinessScale (ratio)Natural resource economicsFood industryFood pricesState (computer science)EconomicsGeographyEconomic growthPolitical scienceEcology

Abstract

fetched live from OpenAlex

The global food landscape is changing rapidly. In 2007–08 food prices soared and remained volatile in the following years, effectively leading to a world food crisis that drove tens of millions of people into poverty and hunger. A phenomenal increase in large-scale farmland acquisitions in developing countries by a range of investors is leaving land rights in question for many small-scale producers while land grabbing is also occurring in the global North. There is also growing corporate concentration in the international food industry, from agricultural input firms to trading firms to production and processing and food retail. A changing global climate with associated unpredictable weather and crop yields complicates this picture, as does a steady increase in the application of agricultural biotechnology worldwide. To counter these global forces, communities around the world are imagining and building alternative locally-based and interconnected food systems grounded in the idea of food sovereignty to ensure food security, ecological sustainability and social justice.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.965

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 head0.075
GPT teacher head0.219
Teacher spread0.144 · 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