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Political Images and Censorship in Germany before 1914

2015/01/01 by Ursula Ε. Koch, Martin Loiperdinger · 1 citation
Social Sciences · #European history and politics #Italian Fascism and Post-war Society

paper · doi:10.1057/9781137316493_5

openalex publication_date 2015/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Until the present day there has been no coherent history of political censorship of the image in Germany. There are two significant explanations for this lacuna. First, the historical fragmentation of the German states and their production facilities (not to mention the turmoil that was the result of World War II) meant that the relevant data in national, regional, communal, or private archives as well as libraries and research institutes is not only widely scattered, but also unclear and incomplete. Second, in contrast to the United States, the field of “visual studies” could only rarely be found at German universities by the end of the twentieth century. 1 This co-authored essay, 2 nolens volens , concentrates on selected geographical cases. In our essay the Kingdom of Prussia, Germany’s biggest and most populated state (excluding Austria), is conceded a special role. The subject of political images and censorship in Germany until 1914, which is subdivided into seven larger and several smaller periods, 3 includes problem areas such as religion and morals as long as they have a political dimension. In a changing, broadly illustrated political and journalistic context, the relevant media and criminal laws are considered as well as the opportunities for the government to intervene economically, for example within the scope of the Trade Regulation. In order not to fall victim to censorship measures of any sort, certain publishers, journalists, and artists decided to use what they called “scissors in the head” (self-censorship). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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