(Re)defining Journalistic Expertise in the Digital Transformation: A Content Analysis of Job Announcements

被引:18
作者
Guo, Lei [1 ]
Volz, Yong [1 ]
机构
[1] Univ Missouri, Sch Journalism, Columbia, MO 65211 USA
关键词
Adaptive expertise; content analysis; innovative expertise; interactional expertise; job announcement; journalistic expertise; traditional expertise; ADAPTIVE EXPERTISE; BIG DATA; FUTURE; PROFESSION; COMMUNITY; KNOWLEDGE; CAREERS; SCIENCE; SKILLS; MEDIA;
D O I
10.1080/17512786.2019.1588147
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
In the last decade or so, the attempt to rethink journalism expertise has been made in the context of a radically changing media environment. While many new journalism skills and knowledge areas have been identified, the existing literature lacks a clear conceptual framework that can comprehensively and systematically examine the many dimensions of journalistic expertise. Drawing on the expertise theory, this study explicates the concept of journalistic expertise and reviews the literature on the disruption, transformation, and reinvention of the journalism industry that forces a rethinking of journalistic expertise. Previous studies based on journalist job announcements are also reviewed and gaps identified. We then present an empirical content analysis of 669 journalist job announcements posted on Indeed.com from 1 July to 31 December 2017. Four types of journalistic expertise are proposed, identified and measured. The journalistic expertise preferences across different journalism platforms and for different journalistic positions are also analyzed. The conceptual implications of this study are addressed and the practical implications for journalists and journalism education are discussed.
引用
收藏
页码:1294 / 1315
页数:22
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