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Record W2129386063 · doi:10.1111/nyas.12594

Validity and reliability of food security measures

2014· review· en· W2129386063 on OpenAlex
Carlo Cafiero, Hugo Melgar‐Quiñonez, Terri J. Ballard, Anne W. Kepple

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

VenueAnnals of the New York Academy of Sciences · 2014
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsMcGill University
Fundersnot available
KeywordsFood securityReliability (semiconductor)Process (computing)Risk analysis (engineering)Computer scienceValidityProcess managementBusinessMathematicsPsychometricsStatisticsAgriculture

Abstract

fetched live from OpenAlex

This paper reviews some of the existing food security indicators, discussing the validity of the underlying concept and the expected reliability of measures under reasonably feasible conditions. The main objective of the paper is to raise awareness on existing trade-offs between different qualities of possible food security measurement tools that must be taken into account when such tools are proposed for practical application, especially for use within an international monitoring framework. The hope is to provide a timely, useful contribution to the process leading to the definition of a food security goal and the associated monitoring framework within the post-2015 Development Agenda.

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)0.008
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.673
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.544
GPT teacher head0.533
Teacher spread0.011 · 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