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Record W3210188060 · doi:10.1016/j.foodpol.2021.102164

Viewpoint: The case for a six-dimensional food security framework

2021· article· en· W3210188060 on OpenAlexafffund
Jennifer A. Clapp (University of Waterloo), William G. Moseley, Barbara Burlingame, Paola Termine

Bibliographic record

VenueFood Policy · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsFood securitySustainabilityAgency (philosophy)Food systemsBusinessFood policyPolitical scienceEnvironmental economicsEnvironmental resource managementEconomicsSociologyEcologySocial science

Abstract

fetched live from OpenAlex

The definition of food security has evolved and changed over the past 50 years, including the introduction of the four commonly cited pillars of food security: availability, access, utilization, and stability, which have been important in shaping policy. In this article, we make the case that it is time for a formal update to our definition of food security to include two additional dimensions proposed by the High Level Panel of Experts on Food Security and Nutrition: agency and sustainability. We show that the impact of widening food system inequalities and growing awareness of the intricate connections between ecological systems and food systems highlight the importance of these additional dimensions to the concept. We further outline the ways in which international policy guidance on the right to food already implies both agency and sustainability alongside the more established four pillars, making it a logical next step to adopt a six dimensional framework for food security in both policy and scholarly settings. We also show that advances have already been made with respect to providing measurements of agency and sustainability as they relate to food insecurity.

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)0.025
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.025
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0090.064
Scholarly communication0.0140.016
Open science0.0030.011
Research integrity0.0070.014
Insufficient payload (model declined to judge)0.0040.001

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 head0.170
GPT teacher head0.479
Teacher spread0.309 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations475
Published2021
Admission routes2
Has abstractyes

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