История оценочных исследований в образовании в США: аналитический обзор
The paper discusses various techniques of studying ideas about the
meanings of word that are common to native speakers of modern
Russian. These ideas sometimes differ significantly from traditional
lexicographic descriptions. Alongside standard surveys where the
informants are addressed directly, more specific experiments are
performed, such as studying the behaviour of those participating in
various linguistic games. The results of these experiments provide
interesting linguistic material which proves useful for lexicographers
working on modern explanatory dictionaries.
Analyzing several Russian nouns denoting everyday life objects, we explain why a word sense frequency dictionary is necessary. Techniques of calculating the approximate frequencies are proposed, based on the analysis of native speaker surveys and the annotation of the most frequent collocations in a large text corpus (we used the huge RuTenTen11 corpus integrated into the Sketch Engine system). A word sense dictionary could be used in a variety of NLP tasks, in particular for a probabilistic word sense disambiguation without available context, in creating second language learning resources, as well as in academic lexicography. Besides, studies of sense sets of polysemous words and their comparative frequencies are important for the linguistic theory, because they shed light on the evolution of the lexical system.
This chapter provides historical evidence of innovation-led structural changes at the sub-national level in high-middle income economies, with particular emphasis on economies characterised by a significant knowledge base and weak institutions. Although manifestly not the outcome of smart specialization policy, the examples of self-discovery, entrepreneurchip and experimentation discussed here describe real-life smart specialization processes. Lessons are drawn to inform S3 policy designs and implementation: (1) Most success stories occurred spontanously, with limited policy interventions, and were led by self-discovery of private and public actors; (2) regional development is usually a by-product of the national or global success of private first movers that can initiate exclaves but may fails to become developed regional clusters; (3) 'Critical mas' of capabilities is a key policy problem at the sub-national level; (4) Collective action and coordination problems impede the S3 process; (5) Complementarity of various regional policies may increase the effectiveness of government support.
The paper discusses various techniques of discovering and describing lexical ambiguity. This is one of the top issues in computational linguistics. A variety of techniques are used for word sense disambiguation, but all of them are based on context. Yet, studying how word senses work without context and what patterns of polysemous words could be found in speakers’ minds also seems an interesting and important issue. The main approaches to WSD with or without context (in narrow and broad sense, including the situational context) are evaluated. The importance of corpora in discovering word senses is substantiated. New experimental data are presented, which allow defining subsets of senses for polysemous words for different speakers and rating the senses in the dictionary. Finally, the paper proposes to distinguish between absolute and relative polysemy and to search for ways of their adequate lexicographic description.
This article is talking about state management and cultural policy, their nature and content in term of the new tendency - development of postindustrial society. It mentioned here, that at the moment cultural policy is the base of regional political activity and that regions can get strong competitive advantage if they are able to implement cultural policy successfully. All these trends can produce elements of new economic development.