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Description: One million manufacturing jobs will be created in the next decade, but manufacturers will be able to fill fewer than half of these job openings due to the skills shortage. One of the determinants of this skill shortage is the misperception of this sector, as manufacturing has been long perceived as dirty work. However, the sector has recently been subject of a deep transformation as a consequence of the adoption of new technologies (Schwab, 2017). This shift is not reflected in today’s manufacturing job titles, since they still rely in outdated conceptions of manual work that do not reflect the advanced set of competences necessary to perform the tasks associated to the new manufacturing job. Our goal in this study is to explore if, and to what extent, linguistic variations in manufacturing job titles (based on the number of words used, the use of linguistic labels, and the reliance on idealised cognitive models) have an impact on the social perception of manufacturing jobs, leading to a better or worse social appreciation of these jobs. We empirically address these issues by surveying 105 native speakers of British English on 36 different manufacturing job titles and test their social perception of these jobs in terms of perceived salary, perceived responsibilities and perceived training. We conducted descriptive and inferential statistical analyses (independent-samples t-test and linear regression analyses). Our results show that multi-word job titles evoke higher wages as well as higher qualifications underlying the tasks performed. In addition to this, the use of linguistic labels such as “machinists”, “operatives” and “technicians” help to form a category that unifies positive attitudes towards the use of technology in manufacturing jobs. However, artisan work in the domain of fashion is still more strongly preferred in the sector of fashion due to its connotations of expertise, luxury, and exclusivity. Implications for policy makers and employers are discussed.

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