Federal Institute for Population Research

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Arbeitshelm vor Ukraineflagge (refer to: Protection seekers from Ukraine: making better use of potential for the German labour market) | Source: © BillionPhotos.com/stock.adobe.com

Press releaseProtection seekers from Ukraine: making better use of potential for the German labour market

New data from the Federal Institute for Population Research show a further increase in the employment rate among Ukrainian refugees. This has almost doubled from 16 per cent in summer 2022 to 30 per cent in spring 2024.

Peer-Reviewed Articles in Scientific JournalsEinstellungen zur Akzeptanz räumlicher Distanz in erwerbsbedingt multilokalen Lebensformen

Rüger, Heiko; Schier, Michaela; Feldhaus, Michael; Ries, Tammy (2014)

Zeitschrift für Familienforschung - Journal of Family Research 26(2): 121–143

Work-related multi-local living arrangements describe those living arrangements in which, due to occupational reasons, at least one partner is absent from the communal residence of the partners or the family for a substantial part of the year. In the context of high requirements concerning spatial flexibility of employees, such living arrangements have become increasingly important. Against this background, this paper examines the acceptance of spatial distance in intimate relationships. Analyses are based on panel data of the “Job Mobilities and Family Lives in Europe” study (2007 and 2010/11), collected in Germany, France, Spain and Switzerland (N=1.189). We used path modelling to conduct a cross-lagged panel analysis. Results show a higher acceptance of spatial distance in intimate relationships in individuals living multi-locally due to work-related spatial mobility requirements. Longitudinal analyses suggest that this correlation is primarily based on adaptation processes. Experiences of multi-local living arrangements lead to attitude changes towards a higher acceptance of spatial distance. However, further selection processes could not be detected, which might partially be explained by a high degree of selectivity at the first point of data collection.

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