Fusco Alessio, Silber Jacques
CEPS/INSTEAD, 3 Avenue de la Fonte, 4364, Esch-sur-Alzette, Luxembourg,
Eur J Health Econ. 2014 Nov;15(8):841-51. doi: 10.1007/s10198-013-0529-5. Epub 2013 Sep 13.
Social polarization refers to the measurement of the distance between different social groups, defined on the basis of variables such as race, religion, or ethnicity. We propose two approaches to measuring social polarization in the case where the distance between groups is based on an ordinal variable, such as self-assessed health status. The first one, the 'stratification approach', amounts to assessing the degree of non-overlapping of the distributions of the ordinal variable between the different population subgroups that are distinguished. The second one, the 'antipodal approach', considers that the social polarization of an ordinal variable will be maximal if the individuals belonging to a given population subgroup are in the same health category, this category corresponding either to the lowest or to the highest health status. An empirical illustration is provided using the 2009 cross-sectional data of the European Union Statistics on Income and Living Conditions (EU-SILC). We find that Estonia, Latvia, and Ireland have the highest degree of social polarization when the ordinal variable under scrutiny refers to self-assessed health status and the (unordered) population subgroups to the citizenship of the respondent whereas Luxembourg is the country with the lowest degree of social polarization in health.
社会两极分化是指对不同社会群体之间距离的衡量，这些群体是根据种族、宗教或民族等变量来界定的。我们提出了两种方法来衡量社会两极分化，适用于群体间距离基于有序变量（如自我评估健康状况）的情况。第一种方法是“分层法”，即评估在不同区分的人口子群体之间有序变量分布的不重叠程度。第二种方法是“对映法”，该方法认为，如果属于特定人口子群体的个体处于相同的健康类别（该类别对应最低或最高健康状况），那么有序变量的社会两极分化将达到最大。我们使用欧盟收入和生活条件统计（EU-SILC）2009年的横截面数据进行了实证说明。我们发现，当所审查的有序变量是自我评估健康状况且（无序的）人口子群体是受访者的公民身份时，爱沙尼亚、拉脱维亚和爱尔兰的社会两极分化程度最高，而卢森堡在健康方面的社会两极分化程度最低。
