Tracing Explanations of Unemployment across Sociodemographic Groups: A Mixed-Methods Content Analysis of German Online News Stories (2003-2015)
(English)Manuscript (preprint) (Other academic)
We first provide a quantitative description of a large collection of digitalized German online news texts (a so-called corpus) spanning 12 years, and find that news stories mentioning unemployment tend to also mention a number of specific sociodemographic groups, namely women, children, the old/young, and, since 2015, refugees. We then utilize computational, count-based modes of manifest content analysis to derive a manageable sample of short text passages that represents the nature of our large corpus but lends itself to in-depth qualitative analysis of latent content. Focusing on this sample of text passages, we investigate whether there are notable differences in how unemployment is explained for each of the identified sociodemographic groups. This is important, because such explanations lie at the heart of popular perceptions of the deservingness of the unemployed and the poor more broadly. Our mixed-methods approach reveals a surprising degree of ambivalence between the portrayal of unemployment as an issue of individual responsibility and self-infliction, as opposed to a matter of circumstance, brought about by forces outside anyone’s personal control within each of the investigated sociodemographic groups. This is not in line with prior research which suggests a much more homogenous attribution of responsibility within presumably more and less deserving groups.
deservingness, unemployment, framing, news, mixed methods, content analysis, corpus, Germany
IdentifiersURN: urn:nbn:se:su:diva-140875OAI: oai:DiVA.org:su-140875DiVA: diva2:1087581
ProjectsThe Evolution of Prejudice
FunderForte, Swedish Research Council for Health, Working Life and Welfare, 2016-07177