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Stephanie Kramer

Researcher at Free University of Berlin

Publications -  8
Citations -  429

Stephanie Kramer is an academic researcher from Free University of Berlin. The author has contributed to research in topics: Social inequality & Population. The author has an hindex of 5, co-authored 6 publications receiving 396 citations.

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Social inequalities in alcohol consumption and alcohol-related problems in the study countries of the EU concerted action 'gender, culture and alcohol problems: a multi-national study'

TL;DR: Social inequalities in the two Latin American countries display a pattern emerging in other research on developing countries: namely that those in the higher educated groups are more likely to consume alcohol in a risky manner.
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Gender and cultural differences in the association between family roles, social stratification, and alcohol use: a European cross-cultural analysis.

TL;DR: It appeared that the social welfare system and gender equity of a country determines to a large extent how education, employment, and family roles are associated with heavy drinking.
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Screening for alcohol-related problems in the general population using CAGE and DSM-IV: Characteristics of congruently and incongruently identified participants

TL;DR: It was found that younger age groups were more likely to meet DSM criteria without reporting CAGE items, and for older age groups, the reverse seems to be true, and heightened awareness is needed when employing the studied instruments in certain groups.
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Developments in alcohol consumption in reunited Germany

TL;DR: Overall frequency of consumption has declined in Germany in the 1990s and drinking behaviour in the two regions has become more similar, and gender and regional differences within the country decreased.
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Die Konstruktion eines empirisch bestimmten Sozialschichtindexes mittels optimaler Skalierung am Beispiel von Deutschland

TL;DR: In this article, a gender-specific metric social status indicator for Germany by using all three single SES-indicators (education, occupation, income) was created using categorical principal components analysis.