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Record W4400663739 · doi:10.18174/656139

Food systems resilience dialogue and pathway development : Jonglei State and Greater Pibor Administrative Area - South Sudan

2024· report· en· W4400663739 on OpenAlexaff
Gerrit-Jan van Uffelen, Pascal Debons, Tony Ngalamu, Arnab Gupta, Julius Kaut, Salah K Jubarah, Augustino Atillio, Marc Antioko, Kok Majok

Bibliographic record

Venuenot available
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsResilience (materials science)State (computer science)GeographyRegional sciencePolitical scienceEnvironmental planningComputer science

Abstract

fetched live from OpenAlex

Food systems in Jonglei State and Greater Pibor Administrative Area (GPAA), South Sudan, are in dire crisis because of multiple shocks and stressors, persisting conflict and violence, climate change, and natural resource deterioration.However, building upon South Sudan's national food systems dialogue, ample opportunities exist to build food systems resilience in Jonglei State and GPAA through strengthening the capacity of people to produce and access nutritious and culturally acceptable food over time and space in the face of natural and/or man-made shocks and stressors.Food systems approaches are increasingly seen as a way forward to develop sustainable food systems in protracted food crisis, as highlighted by the UN Food Systems Summit, the Global Network Against Food Crises, and the Fighting Food Crises along the Nexus Coalition.It is therefore most opportune to act now by investing in an urgently needed transformation towards equitable, inclusive, and sustainable food systems for improved outcomes, in particular food and nutrition security in protracted food crises contexts.For South Sudan this means, in line with the outcomes of its national food systems dialogue, addressing four strategic challenges to transform the country's food systems: 1) strengthening the resilience of food systems in face of current and future shocks and stressors; 2) developing food systems that contribute to social cohesion and peace; 3) ensuring that food systems are based on sustainable use and management of natural resources and produce healthier diets, and; 4) promoting sustainable food supply systems through inclusive value chains and agribusinesses with an eye on youth employment.Governance of food systems takes place at multiple levels and scales but transformation of local food systems will only succeed if communities, civil society organizations, small producers, farmers, and indigenous groups -with their local knowledge, and lived-in experiences -can shape how food is governed.The Jonglei State and GPAA food systems resilience dialogue & pathway development (FoSReD-PaD) provides a contribution to understand local food system dynamics and to strengthen local governance of food systems for improved food systems resilience and outcomes.The Jonglei State and GPAA dialogue envisaged a total of four pathways, in line with South Sudan's national food systems transformation pathways, which together form a roadmap to transform its food systems to become more resilient, better serve the needs of all stakeholders (in particular smallholder farmers/agropastoralists and herders), and improve food and nutrition outcomes for all.

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.004
Scholarly communication0.0080.003
Open science0.0010.014
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.057
GPT teacher head0.244
Teacher spread0.187 · 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 designQualitative
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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