STRUGGLES AGAINST PRECARITY: CHALLENGES IN GERMANY FOR TURKISH NEWCOMERS
Bibliographic record
Abstract
In the last decades, precariousness and precarious labor have become more prominent subjects in academic and policy debates. At the same time, we are observing a surge of right-wing views in society and across political landscapes in industrialized and industrializing countries across the world, putting the blame for increased precarity on the influx of immigrants and making claims about immigration leading to increased labor market competition, supposedly putting local workforce at disadvantage. As the Polish sociologist and philosopher Zygmunt Bauman (2000) has argued, however, the driving force of increasing precarious work conditions as well as new precarious livelihoods has been the neo-liberal restructuring of labor in the last decades. Baumann suggests considering carefully how these conditions of economic exploitation and submission interact with instruments of power (2000, p.48-52) and points out that immigrants are one of the groups most vulnerable to becoming subjects of precarity (see also Standing, 2014). Furthermore, current research in Canada (Frenette & Morisette, 2005) and Germany (Schittenhelm, Schmidtke & Weiß, 2014a; Mayer, 2018a) has shown clearly that among many highly-skilled migrants a majority will be employed in lower-skilled jobs in the country they immigrated to. Following Baumann, this study assumes a more complex connection between phenomena of immigration and precarious labor than dominant societal discourses suggest and examines immigrants’ situations in terms of work conditions and legal statuses in the labor market and society. Using a qualitative approach, it explores specifically how highly-skilled Turkish newcomers experience work-related precariousness, analyzing the characteristics and patterns of their employment conditions. Against the backdrop of recent political developments in Turkey, compared to earlier immigration movements growing wave of skilled immigrants in the last 10 years from Turkey to Germany (especially to Berlin) has increased, especially highly qualified Turkish immigrants who work in the jobs categorized more so with low-qualifications was very fascinating to study. The study draws on conversations with workers from four call centers based in Berlin, Convergys, Sykes, Booking, and Arvato / Majorel in Berlin, all of which provide customer or content management services outsourced from US-American social media, entertainment, and sports equipment companies, such as Facebook, PlayStation, Booking.com and Nike. Theoretically, the study is based on the assumption that migration results in a biographic rupture making it necessary to transfer cultural capital (Bourdieu, 2010). In a first step, the interviews reveal different but interlinked forms of uncertainty underlying the call center employees’ working conditions. A contribution of this study to the understanding of “precariousness” here is to fill this broad concept with empirical evidence from the lives of one particular group and thus making it graspable. In a second step, the paper examines the adaptation mechanisms and strategies migrants have to employ in order to transfer their existing expertise, skills, and personal qualities - from attitudes to worldviews, educational certificates to social networks - of highly educated immigrants to the country of immigration. While newcomer Turkish immigrants lose major parts of their cultural capital, other parts can be transferred. These findings underline the fact that if immigration law and labor laws are not well adapted to migrants’ and the labor markets situation, the vulnerable status of immigrants is likely to make them more vulnerable to precarious work conditions. More broadly, the study argues that listening to the underestimated voices of precarious workers provides important hints for future academic debates on precarity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".