Social and political attitudes (unworried).

Hundreds of studies have been published on fear of crime, but few models offer a unified framework for this social phenomenon. This is the ambition of the model of experiential and expressive fear of crime (EEF) developed in the mid-2000s by a team of British researchers. However, despite its numerous contributions, this original model faces two limitations. First, the different versions of the model present certain discrepancies. Second, the statistical methods used consistently rely on hypothetico-deductive reasoning, which may overlook the existence of certain combinations of variables. The objective of this article, based on a French piece of research, is to revisit this model by combining two different families of statistical methods: multivariate configuration analysis and logistic regression analysis. The first analysis attempts to overcome these two limitations by adopting an inductive approach, which involves studying the multidimensional structure of the data without imposing predefined structures on them. It identifies four classes of respondents, each associated with a specific relationship to experiential fear and expressive fear. If the ‘unworried’ and the ‘worried-dysfunctional’ associate these two dimensions of fear of crime, the ‘anxious’ and the ‘worried-functional’ clearly separate them. By adopting an inferential approach, the second analysis aims to determine the sociodemographic factors of these different groups. It shows that the predictors vary significantly from one group to another and that no variable (not even gender) is a predictor for all groups. These results encourage moving beyond the dichotomous conceptualization (‘worried’/ ‘unworried’), which is still widely used in the study of fear of crime. Systematically identifying these different groups could also help combat fear of crime more effectively by implementing targeted and adapted public policies.已有数百项关于犯罪恐惧（fear of crime）的研究成果发表，但鲜有模型能为这一社会现象提供统一的分析框架。2000年代中期，英国研究团队提出的犯罪体验恐惧与表达恐惧（experiential and expressive fear of crime, EEF）模型，正是旨在填补这一研究空白。尽管该原创模型已作出诸多学术贡献，但仍存在两处局限：其一，模型的不同版本间存在一定差异；其二，其采用的统计方法始终基于假设演绎推理（hypothetico-deductive reasoning），可能会忽略部分变量组合的存在。 本文基于一项法国研究，旨在结合两类不同的统计方法——多变量构型分析（multivariate configuration analysis）与逻辑回归分析（logistic regression analysis）——对该模型进行重新审视。 第一类分析方法采用归纳法（inductive approach），即不预先为数据设定结构，直接探究其多维分布特征，以此克服上述两处局限。该分析识别出四类受访者群体，每类群体均与犯罪恐惧的体验维度及表达维度存在特定关联。 “无焦虑者”与“功能失调型焦虑者”会将犯罪恐惧的这两个维度相互关联，而“焦虑者”与“功能型焦虑者”则明确区分了这两个维度。 第二类分析方法采用推论法，旨在确定不同群体的社会人口学因素（sociodemographic factors）。研究结果显示，不同群体的预测因子存在显著差异，且不存在能够适用于所有群体的预测变量（即便性别也不例外）。 上述研究结果表明，我们应当跳出目前在犯罪恐惧研究中仍被广泛使用的二分法概念化（dichotomous conceptualization）框架。 系统识别这些不同的群体，还有助于通过制定针对性、适配性的公共政策，更有效地应对犯罪恐惧问题。