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首页> 外文期刊>Journal of Cultural Economics >Who is an artist? Heterogeneity and professionalism among visual artists
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Who is an artist? Heterogeneity and professionalism among visual artists

机译：谁是艺术家？ 视觉艺术家之间的异质性和专业性

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The purpose of this article was twofold. Firstly, to investigate the heterogeneity among artists as an occupational category and secondly, to define arts as a profession and thereby to make a distinction between professional artists and amateurs. Artists' income and working conditions have been the subject of several studies, and many different sampling criteria have been used. Scholars have not yet achieved consensus on who should be included in the profession. In this article, we make an innovative contribution to this conversation. By applying a finite mixture model, which combines latent profile and latent class analysis, we have been able to identify different segments of artists in terms of professionalism. Each of these mutually exclusive classes is characterized by a particular income and working situation. We also include a membership function, estimated through a logistic regression, which allows prediction of the probability that an individual will belong to each class, given his/her socioeconomic characteristics. The subject of our study is Danish visual artists. The dataset consists of a combination of register data from Statistics Denmark and data collected from a questionnaire survey with 892 respondents. Based on the artists' civil registration numbers, the two sources have been merged into a unique dataset. Our finite mixture model shows the heterogeneity among artists. Combined with a theoretically definition of arts as a profession, our research propose a distinction between professional artists and amateurs that cuts across categories used in prior literature. The results can be beneficial to cultural policy.
机译：本文的目的是双重的。首先，要调查艺术家之间的异质性作为职业类别，其次是将艺术定义为一个专业，从而区分专业艺术家和业余爱好者。艺术家的收入和工作条件一直是几项研究的主题，并且已经使用了许多不同的抽样标准。学者尚未实现谁应该纳入专业的达成共识。在本文中，我们对这次谈话做出了创新贡献。通过应用结合潜在概况和潜在阶级分析的有限混合物模型，我们能够在专业性方面识别艺术家的不同部分。这些互斥类中的每一个都以特定的收入和工作情况为特征。我们还包括通过逻辑回归估计的会员函数，这允许预测个人属于每个班级的概率，因为他/她的社会经济特征。我们研究的主题是丹麦视觉艺术家。 DataSet包括来自统计数据的寄存器数据的组合，并从92名受访者从调查问卷调查中收集的数据组合。根据艺术家的民事登记号码，这两个来源已被合并到唯一的数据集中。我们的有限混合物模型显示了艺术家之间的异质性。结合理论上的艺术定义作为一个专业，我们的研究提出了跨文学中使用的类别的专业艺术家和业余爱好者之间的区别。结果可能有利于文化政策。

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