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This chapter analyses the impact of political decentralization in a state on the position of ethnic and linguistic minorities, in particular with regard to the role of parliamentary assemblies in the political system. It relates a number of typical functions of parliaments to the specific needs of minorities and their languages. The most important of these functions are the representation of the minority and responsiveness to the minority’s needs. The chapter then discusses six examples from the European Union (and Norway) which prototypically represent different types of parliamentary decentralization: the ethnically defined Sameting in Norway and its importance for the Sámi population, the Scottish Parliament and its role for speakers of Scottish Gaelic, the German regional parliaments of the Länder of Schleswig-Holstein and Saxony and their impact on the Frisian and Sorbian minorities respectively, the autonomy of predominantly German-speaking South Tyrol within the Italian state, and finally the situation of the speakers of Latgalian in Latvia, where a decentralized parliament is missing. The chapter also makes suggestions on comparisons of these situations with minorities in Russia. It finally argues that political decentralization may indeed empower minorities to gain a greater voice in their states, even if much ultimately depends on individual factors in each situation and the attitudes by the majority population and the political center.
In this article, we explore the feasibility of extracting suitable and unsuitable food items for particular health conditions from natural language text. We refer to this task as conditional healthiness classification. For that purpose, we annotate a corpus extracted from forum entries of a food-related website. We identify different relation types that hold between food items and health conditions going beyond a binary distinction of suitability and unsuitability and devise various supervised classifiers using different types of features. We examine the impact of different task-specific resources, such as a healthiness lexicon that lists the healthiness status of a food item and a sentiment lexicon. Moreover, we also consider task-specific linguistic features that disambiguate a context in which mentions of a food item and a health condition co-occur and compare them with standard features using bag of words, part-of-speech information and syntactic parses. We also investigate in how far individual food items and health conditions correlate with specific relation types and try to harness this information for classification.