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Record W3125164675 · doi:10.1080/02255189.2020.1858761

Strengthening resilience in response to COVID-19: a call to integrate social reproduction in sustainable food systems

2021· article· en· W3125164675 on OpenAlexvenueno aff
Fiorella Picchioni, June Y. T. Po, Lora Forsythe

Bibliographic record

VenueCanadian Journal of Development Studies/Revue canadienne d études du développement · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsReproductionResilience (materials science)Food systemsCoronavirus disease 2019 (COVID-19)Food insecuritySocial reproductionPsychological resilienceSustainabilityEnvironmental ethicsWork (physics)SociologyFood securityPolitical scienceSocial sciencePsychologyEcologySocial psychologySocial capitalBiologyMedicine

Abstract

fetched live from OpenAlex

COVID-19 has revealed new tensions and exacerbated old fragilities in global food systems, characterised by the systemic socio-economic reliance on invisible, unpaid and devalued work. We argue that, in the same way environmental concerns have become integral to the Sustainable Food Systems agenda, a social reproduction approach, informed by geographies of care, are essential for a critical analysis and the search for alternatives. By linking analytical concepts to examples from social movements, the commentary calls for a paradigm shift and a new research agenda involving these critical perspectives on resilient and sustainable food systems.

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)0.021
metaresearch head score (Gemma)0.024
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: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0150.067
Scholarly communication0.0150.013
Open science0.0040.012
Research integrity0.0210.026
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 head0.046
GPT teacher head0.247
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 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
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

Citations16
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Development Studies/Revue canadienne d études du développementSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207