Data Scientists' Identity Work

Omnivorous Symbolic Boundaries in Skills Acquisition

Datos Bibliográficos

ID2374486
AutoresNetta Avnoon (0000-0002-3758-2097, The Hebrew University of Jerusalem, Israel, autor de correspondencia)
Año2021
Volumen35
Número2
Páginas332-349
Fecha de publicación2021-04-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaWork Employment and Society (JOURNAL)
Identificadores de la revistaISSN: 0950-0170 • E-ISSN: 1469-8722
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/0950017020977306
OpenAlexW3118739323
IdiomaEN
Citas recibidas19
Referencias citadas60

Drawing on theories from the sociology of work and the sociology of culture, this article argues that members of nascent technical occupations construct their professional identity and claim status through an omnivorous approach to skills acquisition. Based on a discursive analysis of 56 semi-structured in-depth interviews with data scientists, data science professors and managers in Israel, it was found that data scientists mobilise the following five resources to construct their identity: (1) ability to bridge the gap between scientist's and engineer's identities; (2) multiplicity of theories; (3) intensive self-learning; (4) bridging technical and social skills; and (5) acquiring domain knowledge easily. These resources diverge from former generalist-specialist identity tensions described in the literature as they attribute a higher status to the generalist-omnivore and a lower one to the specialist-snob

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