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Record W3206567966 · doi:10.3390/land10101090

Comprehensive Food System Planning for Urban Food Security in Nanjing, China

2021· article· en· W3206567966 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLand · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of WaterlooBalsillie School of International Affairs
FundersSocial Sciences and Humanities Research Council of CanadaInternational Development Research Centre
KeywordsFood securityChinaBusinessEnvironmental planningFood insecurityFood systemsUrban planningEconomic shortageEconomic growthGeographyEnvironmental resource managementEconomicsAgricultureGovernment (linguistics)EngineeringCivil engineering

Abstract

fetched live from OpenAlex

Food system planning is important to achieve the goal of “zero hunger” in the UN’s 2030 Agenda for Sustainable Development (UN, 2016). However, discussion about comprehensive planning for food security is scarce and little is known about the situation in Chinese cities. To narrow this gap, this study collected and analyzed four medium-term plans and two annual plans for the “vegetable basket project” in Nanjing, China. This study examines the strategies for urban food security in Nanjing to shed light on how the city developed a comprehensive approach to food system planning over the past three decades. The evolution of incremental food system planning in Nanjing provides valuable lessons for other cities facing food security challenges and shortages of financial resources. Reducing food insecurity is an ongoing challenge for the city governments in the Global South and comprehensive planning is a useful tool for addressing the challenge of urban 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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.170

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)0.0000.000

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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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