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Record W2902541872 · doi:10.5539/jsd.v11n6p205

Livelihood Assets and Activities in Two East Coast Communities of Zanzibar and Implications for Vulnerability to Climate Change and Non-Climate Risks

2018· article· en· W2902541872 on OpenAlexvenueno aff
Makame Omar Makame, Layla Ali Salum, Richard Y. M. Kangalawe

Bibliographic record

VenueJournal of Sustainable Development · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodAdaptive capacityVulnerability (computing)Diversification (marketing strategy)Climate changeNatural resource economicsGeographyAsset (computer security)BusinessSocioeconomicsEnvironmental resource managementAgricultureEconomicsEcology

Abstract

fetched live from OpenAlex

Climate variability related events such as drought and associated food shortages are not new along the coast of Zanzibar, but are projected to increase with the impacts of global climate change. This paper examines the ‘internal’ characteristics that make Zanzibar’s coastal communities vulnerable to these and other changes, focusing on the factors that affect adaptive capacity (i.e. household and community assets) and sensitivity (i.e. livelihood activities and diversification). The sustainable livelihood approach and framework, especially the five capitals or assets, provided a lens to examine households’ capital stocks and the factors influencing access to these, as well as the outcomes for livelihood activities. Access to different capitals and assets were found to affect the range and choices of livelihood activities available to households as well as their ability to cope and adapt to existing and new risk. Our analysis shows how households on the drier and harsher east coast of the Zanzibar islands are particularly sensitive to climate variability and change in concert with other livelihoods challenges. This is primarily due to their high dependence on natural-resource based livelihood activities, which are already facing pressures. Moreover, low levels of most livelihood capitals limit the choices households have and undermine their adaptive capacity and ability to bounce back from climate and other shocks and stressors.

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)0.002
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 score0.185
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.139
GPT teacher head0.377
Teacher spread0.238 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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