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Record W3040897710 · doi:10.18192/potentia.v7i0.4425

Food Security and Climate Change in Sub-Saharan Africa

2016· article· en· W3040897710 on OpenAlexaffvenue
Chase McGowan

Bibliographic record

VenuePotentia Journal of International Affairs · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsCarleton University
Fundersnot available
KeywordsFood securityClimate changeAgriculturePolitical economy of climate changeBusinessFood systemsPolitical scienceNatural resource economicsEnvironmental resource managementDevelopment economicsEconomic growthGeographyEnvironmental planningEconomicsEcology

Abstract

fetched live from OpenAlex

Climate change is predicted to have a detrimental impact on food security throughout the world, but the poorest regions are likely to be the most affected. The Food and Agriculture Organization identifies four aspects of food security: availability, access, stability and utilization. This literature review examines the predicted impacts of climate change on food security in Sub-Saharan Africa. First, an analysis of the scientific literature was undertaken to investigate the potential impact of climate change on each of these four aspects. Second, policies relating to food security and climate change of key UN bodies, international non-profit organizations, and national governments in Sub-Saharan Africa were examined. Overall, there is extensive evidence that climate change will negatively impact each of the four aspects of food security in Sub-Saharan Africa. Until now, international organizations and national governments have failed to adopt comprehensive policies to adapt to climate change. To be effective, efforts to address the problem should combine social and development aspects.

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)0.000
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 score0.850
Threshold uncertainty score0.381

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 head0.028
GPT teacher head0.236
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2016
Admission routes2
Has abstractyes

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