Journalists’ professional self-representations: a Portuguese perspective based on the contribution made by the sociology of professions

• Main Author: Quintanilha, T. L.
• Publication Date: 2019
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10071/17251
• topic: Ambivalence in professions; Deprofessionalisation and proletarianisation; Journalism; Portugal; Profession and professionalism; Sociology of professions

The deregulation of labour markets and the proliferation of precarious labour contracts are making it more difficult for journalists to retain occupational control of their professional practice, and this is in turn forcing them to renegotiate their contract with society. At the same time, journalists’ authority as gatekeepers is constantly being eroded and is being replaced by ‘gatewatching’ – a practice underpinned by a more participatory audience that plays the part of content curator. That authority is also being challenged by the redefinition of the barriers between news producers and consumers brought about by the advent en masse of networked journalists. This is the perspective from which this article addresses the dynamics of change in the journalist’s profession, which is further heightening the uncertainty and angst felt in the structures of professional performance. Taking professional self-representation as a starting point and framing it against the background of the leading ideas postulated in the sociology of professions, the article’s goal is to paint a picture of the journalistic profession in Portugal and to understand how journalists evaluate their profession, the structures of professionalism and the dynamics of deprofessionalisation and proletarianisation, while situating those perceptions within the theory of ‘ambivalence in professions’. The primary methodology is quantitative, with longitudinal analyses of the main data gathered from surveys of journalists based on three intentional non-probabilistic samples (2010, 2012, and 2016).