Department of Economics, University of Sheffield, Sheffield, United Kingdom.
Sheffield Methods Institute, University of Sheffield, Sheffield, United Kingdom.
PLoS One. 2024 Aug 26;19(8):e0305774. doi: 10.1371/journal.pone.0305774. eCollection 2024.
Several studies have explored the relationship between socially constructed neighbourhood boundaries (henceforth social boundaries) and ethnic tensions. To measure these relationships, studies have used area-level demographic data to predict the location of social boundaries and their characteristics. The most common approach uses areal wombling to locate neighbouring areas with large differences in residential characteristics. Areas with large differences (or higher boundary values) are used as a proxy for well-defined social boundaries. However, to date, the results of these predictions have never been empirically validated. This article presents results from a simple discrete choice experiment designed to test whether the areal wombling approach to boundary detection produces social boundaries that are recognisable to local residents and experts as such. We conducted a small feasibility trial with residents and experts in Rotherham, England. Our results shows that participants were more likely to recognise boundaries with higher boundary values as local community borders. We end with a discussion on the scalability of the design and suggest future improvements.
已有多项研究探索了社会构建的邻里边界（以下简称社会边界）与族裔紧张之间的关系。为了衡量这些关系，研究人员使用区域人口统计数据来预测社会边界的位置及其特征。最常见的方法是使用区域划分来定位居住特征差异较大的相邻区域。差异较大的区域（或更高的边界值）被用作明确界定的社会边界的替代指标。然而，迄今为止，这些预测结果从未经过实证验证。本文介绍了一项简单的离散选择实验的结果，该实验旨在测试区域划分方法是否能识别出当地居民和专家认可的社会边界。我们在英格兰罗瑟勒姆的居民和专家中进行了一项小型可行性试验。我们的结果表明，参与者更有可能将具有较高边界值的边界识别为当地社区边界。最后，我们讨论了设计的可扩展性，并提出了未来的改进建议。
