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Record W2600589622 · doi:10.5539/jsd.v10n2p218

Gender and Resilience to Climate Variability in Pastoralists Livelihoods System: Two Case Studies in Kenya

2017· article· en· W2600589622 on OpenAlexfundvenueno aff
Nancy Omolo, Paramu Mafongoya, Oscar Ngesa

Bibliographic record

VenueJournal of Sustainable Development · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
FundersDepartment for International DevelopmentInternational Development Research Centre
KeywordsLivelihoodPastoralismVulnerability (computing)Adaptive capacityPsychological resilienceGeographyClimate changeContext (archaeology)SocioeconomicsEnvironmental resource managementResilience (materials science)LivestockEcologyAgricultureSociologyEconomicsPsychology

Abstract

fetched live from OpenAlex

Recurrent droughts due to climate change has led to vulnerability of the pastoralist communities, leading to loss of assets and food insecurity. Climate change will have different impacts on women and men’s livelihoods. Building resilience at individual, household and community level will largely depend on the suitability of interventions to the local context, particularly in relation to the social dynamics and power relations that create differences in vulnerability. Most of the research have focused on national and regional studies. The impact of climate change will not be uniformly distributed in countries within Africa or within the same country. This specific research focuses on two diverse ecological zones at the local level in the same County of Turkana in north western Kenya: agro-pastoral zone and primary pastoral zone. This paper aims to evaluate women and men’s adaptive capacity to climate variability in Turkana, north-western Kenya. It is evident that increasing resilience can be realised by reducing vulnerabilities and increasing adaptive capacity. The results revealed that agro-pastoralists are more resilient to climate change than primary pastoralists. Male headed household are more resilient than female headed households. Access to basic services is contributing more in the resilience score than assets, gender of house hold head and age. Generally, few families in this region have very high resilience score.

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)0.003
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 score0.018
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.001
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 head0.022
GPT teacher head0.296
Teacher spread0.274 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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