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.

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.

Who is an artist? Heterogeneity and professionalism among visual artists

Baldin, Andrea
;
2021-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3735183
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