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    Helene Schjerfbecks Selbstbildnisse – an den Grenzen des Ich

    Eine hermeneutische Studie zum Porträt im 19. und 20. Jahrhundert

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    Author(s)
    Landmann, Annika
    Collection
    AG Universitätsverlage
    Language
    German
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    Abstract
    The Finnish painter Helene Schjerfbeck (1862–1946) is one of the most famous art-ists in Finland, whereas outside the Nordic countries her works are still presented as a discovery. This thesis focuses on her self-portraits that create a core element of her oeuvre. A close reading of the self-portraits gives insight into the wide range of topics, that are inherent in the paintings and drawings. A characteristic of Schjerfbeck’s imagery is a non finito aesthetic, which is more than just a matter of style. Rather, this specific aesthetic contributes to a multi-layered depiction of the self. A closer look at the historical context shows how some of her commissioned self-portraits were part of a public image of the artist, that had its origin in the first decades of the 20th century. Other works, some of them not meant for the public, give insight into a more intimate reflection, that offers visual approaches to gender, otherness, death and creativity. References to works of Tyko Sallinen, Edvard Munch, Pablo Picasso, Käthe Kollwitz or Francis Bacon help to understand Schjerfbeck’s unique visual meditations on existential questions of humanity.
    URI
    https://library.oapen.org/handle/20.500.12657/57717
    Keywords
    Modern painting; Self-portraits; Portrait art; Sweden; Finland
    DOI
    10.15460/HUP.HHD.002.190
    ISBN
    9783943423631, 9783943423631
    Publisher
    Hamburg University Press
    Publication date and place
    Hamburg, 2018
    Classification
    Theory of art
    Pages
    264
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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