Skip to content

University of Siegen's research reveals that trainees with names of foreign origin face disadvantages

Job seekers with a migrant background face more difficulties in securing apprenticeships, according to a study by the University of Siegen, with origins appearing to hold more weight than performance in recruitment decisions.

University of Siegen research reveals disadvantage faced by trainees carrying non-German names
University of Siegen research reveals disadvantage faced by trainees carrying non-German names

University of Siegen's research reveals that trainees with names of foreign origin face disadvantages

University of Siegen Study Highlights Discrimination Against Job Applicants with Migrant Backgrounds

A new study conducted by the University of Siegen has found evidence of discrimination against job applicants with migrant backgrounds in the German training market. The study, which analysed over 50,000 email inquiries to companies offering training places and surveyed around 700 companies, revealed that applicants with non-German-sounding names receive fewer responses to their applications compared to those with German-sounding names.

The study's findings indicate a potential issue of discrimination in the job market for applicants with migrant backgrounds. Professor Dr. Ekkehard Köhler from the University of Siegen calls for action, stating "We cannot afford to waste potential."

The study highlights a problematic disadvantage in the crafts sector, which is suffering from a lack of young talent. For instance, Yusuf Kaya (Turkish) received 52 responses, while Lukas Becker (German) received 67 responses out of 100 applications. Similarly, Habiba Mahmoud (Arabic) received 36 responses, and Ariel Rubinstein (Hebrew) received 54 responses, compared to Ivan Smirnov (Russian) who received 56 responses.

The study offers concrete recommendations on how politics and practice can counter the disadvantage of applicants with migrant backgrounds. The approach suggested by the study is to address the root causes of the disadvantage rather than focusing solely on applicant performance.

The study recommends addressing the disadvantage faced by job applicants with migrant backgrounds by tackling companies' concerns about language barriers, cultural distance, residence permit issues, and additional administrative burdens. Specifically, the study suggests providing language support and integration training to applicants to reduce perceived language and cultural gaps. Simplifying administrative procedures related to residence permits to minimize extra work for companies is also proposed. Offering informational resources or assistance to companies to better manage bureaucratic concerns linked to migrant hires is another recommendation.

While the study does not list precise policy prescriptions, the key implication is that reducing fears related to language skills, cultural integration, and bureaucratic complexity could help improve migrant applicants' chances. The study found that origin matters more than performance in hiring outcomes, suggesting that the disadvantage for applicants with migrant backgrounds is not offset by better academic performance or social engagement.

The study's findings are concerning, but they also provide a starting point for addressing the issue of discrimination against job applicants with migrant backgrounds in the German training market. By taking action to reduce the barriers faced by migrant applicants, we can help ensure that everyone has an equal opportunity to succeed in their careers.

[1] University of Siegen study, 2021.

Education and self-development cannot be fully achieved if discrimination persists in job applications, particularly for those with migrant backgrounds, as highlighted by the University of Siegen's 2021 study. Addressing the root causes of discrimination, such as language barriers, cultural distance, residence permit issues, and administrative burdens, is crucial to creating an equal opportunity for job applicants with diverse backgrounds.

Read also:

    Latest