104 lines
3.4 KiB
YAML
104 lines
3.4 KiB
YAML
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abstract: 'Urban decision-makers in South Africa face growing challenges related to
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rapidly expanding populations and a changing climate. To help target
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limited resources, municipalities have begun to conduct climate change
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vulnerability assessments. Many of these assessments take a holistic
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approach that combines both physical hazard exposure and the underlying
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socio-economic conditions that predispose populations to harm (i.e.,
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social vulnerability). Given the increasing use of socio-economic
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conditions in climate change vulnerability analyses, this paper seeks to
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explore two key research questions: 1) can the spatial distribution of
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relative social vulnerability be estimated in six mostly urban South
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African municipalities, and if so, 2) how sensitive are the results to a
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range of subjective methodological choices often required when
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implementing this type of analysis. Here, social vulnerability is
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estimated using socio-economic and demographic data from the 2001 and
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2011 South African censuses. In all six municipalities, social
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vulnerability varies spatially, driven primarily by differences in
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income, assets, wealth, employment and education, and secondarily by
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differences in access to services and demographics. Even though social
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vulnerability is estimated from a wide array of population
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characteristics, the spatial distribution is surprising similar to that
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of the percent of working-age individuals making less than 800 rand per
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month. Areas with high percentages of previously disadvantaged, extended
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family, and informal households tend to display relatively higher levels
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of social vulnerability. In fact, demographics (e.g., race, language,
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age) are often highly correlated with other characteristics that have
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direct ties to social vulnerability (e.g., income, employment,
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education). The spatial patterns of relative social vulnerability are
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similar in 2001 and 2011. However, there is some evidence social
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vulnerability is relatively lower in 2011. While the choice of input
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data and aggregation method can affect the spatial distribution of
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social vulnerability, the general spatial patterns appear to be fairly
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robust across a number of subjective choices related to methodological
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and aggregation approach, spatial resolution, and input data.'
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affiliation: 'Apotsos, A (Corresponding Author), Williams Coll, Geosci Dept, Clark
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Hall,947 Main St, Williamstown, MA 01267 USA.
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Apotsos, Alex, Williams Coll, Geosci Dept, Clark Hall,947 Main St, Williamstown,
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MA 01267 USA.'
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author: Apotsos, Alex
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author-email: aa13@williams.edu
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author_list:
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- family: Apotsos
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given: Alex
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da: '2023-09-28'
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doi: 10.1016/j.apgeog.2019.02.012
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eissn: 1873-7730
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files: []
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issn: 0143-6228
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journal: APPLIED GEOGRAPHY
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keywords: Social vulnerability; South Africa; Urban municipalities; Mapping
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keywords-plus: 'CLIMATE-CHANGE ADAPTATION; ADAPTIVE CAPACITY; NATURAL HAZARDS;
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ASSESSMENTS; VARIABILITY; INDICATORS; CHALLENGES; HOUSEHOLDS; DYNAMICS;
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LEVEL'
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language: English
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month: APR
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number-of-cited-references: '69'
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pages: 86-101
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papis_id: 37854f606fb529dbbfcd4cbd40524e5a
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ref: Apotsos2019mappingrelative
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times-cited: '16'
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title: Mapping relative social vulnerability in six mostly urban municipalities in
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South Africa
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type: Article
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unique-id: WOS:000464479200008
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usage-count-last-180-days: '3'
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usage-count-since-2013: '20'
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volume: '105'
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web-of-science-categories: Geography
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year: '2019'
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