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Record W2792670219 · doi:10.1177/0030727018760601

Informational barriers, quality assurance and the scaling up of complementary food supply chains in Sub-Saharan Africa

2018· article· en· W2792670219 on OpenAlex
Lisa F. Clark, Jill E. Hobbs

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

VenueOutlook on Agriculture · 2018
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsBusinessSupply chainCredenceQuality assuranceQuality (philosophy)StakeholderSustainabilityFood supplyFood chainIndustrial organizationFood qualityMarketingEnvironmental economicsEconomicsAgricultural economicsComputer science

Abstract

fetched live from OpenAlex

This article examines how effective quality assurance mechanisms can help address three challenges facing scaling-up efforts in supply chains for complementary foods in Sub-Saharan Africa (SSA): sourcing, market size and consumer trust. We use supply chain analysis to evaluate how stakeholder actions and relationships influence the dynamics of complementary food markets in SSA. We argue that effective signalling of credence attributes via credible quality assurance can contribute to the sustainability of local complementary food supply chains and once established, may contribute to the long-term affordability, accessibility and availability of these foods in SSA. The article concludes by stressing that allocating resources for establishing or further implementing regional and/or state-level quality assurance mechanisms for food safety and quality requires the coordination of stakeholder actions to address food insecurity across SSA.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.321

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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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