Add wos sample results library

02-data/intermediate/wos_sample/686f026983b6b2a221854a9b67bc4ad2-apotsos-alex/info.yaml

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