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Preface
(2015)
Russia, its languages and its ethnic groups are for many readers of English surprisingly unknown territory. Even among academics and researchers familiar with many ethnolinguistic situations around the globe, there prevails rather unsystematic and fragmented knowledge about Russia. This relates to both the micro level such as the individual situations of specific ethnic or linguistic groups, and to the macro level with regard to the entire interplay of linguistic practices, ideologies, laws, and other policies in Russia. In total, this lack of information about Russia stands in sharp contrast to the abundance of literature on ethnolinguistic situations, minority languages, language revitalization, and ideologies toward languages and multilingualism which has been published throughout the past decades.
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.
This is the first comprehensive volume to compare the sociolinguistic situations of minorities in Russia and in Western Europe. As such, it provides insight into language policies, the ethnolinguistic vitality and the struggle for reversal of language shift, language revitalization and empowerment of minorities in Russia and the European Union. The volume shows that, even though largely unknown to a broader English-reading audience, the linguistic composition of Russia is by no means less diverse than multilingualism in the EU. It is therefore a valuable introduction into the historical backgrounds and current linguistic, social and legal affairs with regard to Russia’s manifold ethnic and linguistic minorities, mirrored on the discussion of recent issues in a number of well-known Western European minority situations.
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.
We examine the combination of pattern-based and distributional similarity for the induction of semantic categories. Pattern-based methods are precise and sparse while distributional methods have a higher recall. Given these particular properties we use the prediction of distributional methods as a back-off to pattern-based similarity. Since our pattern-based approach is embedded into a semi-supervised graph clustering algorithm, we also examine how distributional information is best added to that classifier. Our experiments are carried out on 5 different food categorization tasks.