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Food Is Different During the Pandemic

2022· article· en· W4281718532 on OpenAlexfundaboutno aff
Anna Jastrzębiec-Witowska

Bibliographic record

VenueAd Americam · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
FundersEconomic Research ServiceDalhousie UniversityAgriculture and Agri-Food CanadaGovernment of CanadaU.S. Department of Agriculture
KeywordsFood securityPandemicFood systemsDevelopment economicsWork (physics)Coronavirus disease 2019 (COVID-19)Face (sociological concept)Political scienceBusinessEconomic growthGeographyAgricultureEconomicsSociologyEngineeringSocial scienceMedicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has left no area of human life unaffected and the food system in its global, regional, or micro manifestations is not an exception. The images of empty store shelves caused by lockdowns stirred a lot of anxiety among consumers in the so-called First World. At the same time, thousands of miles away, in the developing and underdeveloped countries, where having a meal is never taken for granted, people suffered the harshest consequences of any pandemic-related instability in the food system. Both these realities deserve intellectual reflection, with the former being far more intricate than its media portrayals and therefore will be explored further in this work. This paper aims to study the COVID-19 impact on food systems in developed countries such as the United States and Canada, as well as the challenges to the food security they face during the pandemic. It offers a top-down approach, starting with the definition of food security, and highlighting some crucial aspects of food access and food availability, which has been compromised by the spread of coronavirus in the two countries. Detailed analysis of responses to the pandemic-related food security problems in both countries will be offered as well. The right to food is presented here as a human right, and the links between that right and the concept of food security are brought out. The pandemic wreaked havoc on food security in many parts of the world, including the affluent, but at the same time revealed its fragility and the need for continuous monitoring, re-assessment, and improvement through more effective food programs. The emerging sliver of hope for a more just postpandemic food system should not be ignored.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.240
Teacher spread0.201 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes2
Has abstractyes

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