18 resultados para Channel of academic studies


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This study deals with how ethnic minorities and immigrants are portrayed in the Finnish print media. The study also asks how media users of various ethnocultural backgrounds make sense of these mediated stories. A more general objective is to elucidate negotiations of belonging and positioning practices in an increasingly complex society. The empirical part of the study is based on content analysis and qualitative close reading of 1,782 articles in five newspapers (Hufvudstadsbladet, Vasabladet, Helsingin Sanomat, Iltalehti and Ilta-Sanomat) during various research periods between 1999 and 2007. Four case studies on print media content are followed up by a focus group study involving 33 newspaper readers of Bosnian, Somalian, Russian, and 'native' Finnish backgrounds. The study draws from different academic and intellectual traditions; mainly media and communication studies, sociology and social psychology. The main theoretical framework employed is positioning theory, as developed by Rom Harré and others. Building on this perspective, situational self-positioning, positioning by others, and media positioning are seen as central practices in the negotiation of belonging. In support of contemporary developments in social sciences, some of these negotiations are seen as occurring in a network type of communicative space. In this space, the media form one of the most powerful institutions in constructing, distributing and legitimising values and ideas of who belongs to 'us', and who does not. The notion of positioning always involves an exclusionary potential. This thesis joins scholars who assert that in order to understand inclusionary and exclusionary mechanisms, the theoretical starting point must be a recognition of a decent and non-humiliating society. When key insights are distilled from the five empirical cases and related to the main theories, one of the major arguments put forward is that the media were first and foremost concerned with a minority actor's rightful or unlawful belonging to the Finnish welfare system. However, in some cases persistent stereotypes concerning some immigrant groups' motivation to work, pay taxes and therefore contribute are so strong that a general idea of individualism is forgotten in favour of racialised and stagnated views. Discussants of immigrant background also claim that the positions provided for minority actors in the media are not easy to identify with; categories are too narrow, journalists are biased, the reporting is simplifying and carries labelling potential. Hence, although the will for the communicative space to be more diverse and inclusive exists — and has also in many cases been articulated in charters, acts and codes — the positioning of ethnic minorities and immigrants differs significantly from the ideal.

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Gene expression is one of the most critical factors influencing the phenotype of a cell. As a result of several technological advances, measuring gene expression levels has become one of the most common molecular biological measurements to study the behaviour of cells. The scientific community has produced enormous and constantly increasing collection of gene expression data from various human cells both from healthy and pathological conditions. However, while each of these studies is informative and enlighting in its own context and research setup, diverging methods and terminologies make it very challenging to integrate existing gene expression data to a more comprehensive view of human transcriptome function. On the other hand, bioinformatic science advances only through data integration and synthesis. The aim of this study was to develop biological and mathematical methods to overcome these challenges and to construct an integrated database of human transcriptome as well as to demonstrate its usage. Methods developed in this study can be divided in two distinct parts. First, the biological and medical annotation of the existing gene expression measurements needed to be encoded by systematic vocabularies. There was no single existing biomedical ontology or vocabulary suitable for this purpose. Thus, new annotation terminology was developed as a part of this work. Second part was to develop mathematical methods correcting the noise and systematic differences/errors in the data caused by various array generations. Additionally, there was a need to develop suitable computational methods for sample collection and archiving, unique sample identification, database structures, data retrieval and visualization. Bioinformatic methods were developed to analyze gene expression levels and putative functional associations of human genes by using the integrated gene expression data. Also a method to interpret individual gene expression profiles across all the healthy and pathological tissues of the reference database was developed. As a result of this work 9783 human gene expression samples measured by Affymetrix microarrays were integrated to form a unique human transcriptome resource GeneSapiens. This makes it possible to analyse expression levels of 17330 genes across 175 types of healthy and pathological human tissues. Application of this resource to interpret individual gene expression measurements allowed identification of tissue of origin with 92.0% accuracy among 44 healthy tissue types. Systematic analysis of transcriptional activity levels of 459 kinase genes was performed across 44 healthy and 55 pathological tissue types and a genome wide analysis of kinase gene co-expression networks was done. This analysis revealed biologically and medically interesting data on putative kinase gene functions in health and disease. Finally, we developed a method for alignment of gene expression profiles (AGEP) to perform analysis for individual patient samples to pinpoint gene- and pathway-specific changes in the test sample in relation to the reference transcriptome database. We also showed how large-scale gene expression data resources can be used to quantitatively characterize changes in the transcriptomic program of differentiating stem cells. Taken together, these studies indicate the power of systematic bioinformatic analyses to infer biological and medical insights from existing published datasets as well as to facilitate the interpretation of new molecular profiling data from individual patients.

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This study addresses the challenge of analyzing interruption in spoken interaction. It begins with my observation of eight hours of academic group work among speakers of English as a lingua franca (ELF) in a university course. Unlike the common findings of ELF research which underscore the cooperative orientation of ELF users, this particular group gave strong impressions of interruption and uncooperativeness as they prepared a scientific group presentation. In the effort to investigate these impressions, I found that no satisfactory method exists for systematically identifying and analyzing interruptions. A useful tool was found in Linear Unit Grammar or LUG (Sinclair & Mauranen 2006), which analyzes spoken interaction prospectively as linear text. In the course of transcribing one of the early group work meetings, I developed a model of LUG-based criteria for identifying individual instances of interruption. With this system in place, I was then able to evaluate the aggregate occurrences of interruption in the group work and identify co-occurring interactive features which further influenced the perception of uncooperativeness. Finally, these aggregate statistics directed a return to the data and a contextually sensitive, qualitative analysis. This research cycle illuminates the interactive features which contributed to my own impressions of uncooperativeness, as well as the group members orientations to their own interruptive practice.