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Record W7028159126

Dynamics of Rural-Urban Food Systems in Southern Africa

2022· dissertation· en· W7028159126 on OpenAlexfundno aff

Bibliographic record

VenueUA Campus Repository (The University of Arizona) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicGerman Social Sciences and History
Canadian institutionsnot available
FundersU.S. Geological SurveyQueen's UniversityNational Science Foundation
KeywordsPopulationFood securityUrbanizationEctothermContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Millions of households in Africa sit at the confluence of rapid urbanization and challenging climate conditions - making them especially vulnerable to food insecurity. Food systems in Africa must provide for an increasing number of urban residents, whilst coping with the impacts of climate variability and change. As urbanization processes continue to intensify, the connectivity between rural and urban areas is particularly important for both food and livelihood security yet remains critically understudied. Secondary urban areas are of particular concern, as they outnumber large cities in both number and cumulative population but are often marginalized in research and policy. These smaller urban areas are often the most tightly connected to rural agricultural production, in proximity and their vulnerability to agricultural shocks. How food systems operate across the rural-urban continuum is of central importance for food and livelihood security. Broadly, this dissertation examines these dynamics, seeking to understand how climate shocks in rural agroecosystems impact urban food security, as well as the reciprocal processes through which urban growth and urban food demand alter the function of rural-urban food systems. This work focuses on rapidly urbanizing secondary urban areas in southern Africa, which represent 85% of the total urban population in the region. The goals of this dissertation are threefold: 1) Quantify the patterns and drivers of urban population growth in secondary urban areas; 2) Examine the relationships between climate, geographic, and population-based variables, and food price volatility in urban areas and 3) Identify important rural-urban linkages and household food sourcing strategies used to cope with food price volatility in secondary urban areas. Across southern Africa, communities and nations are struggling to meet increasing food demand across a range of spatial scales. This dissertation highlights the need for solutions to cope with the impacts of climate change and rapid urbanization. More than half of the global population currently lives in urban areas, and the functioning of rural-urban food systems is of critical importance to ensure sustainable development and food security.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.200
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

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