Immigration, security and the public debate on US language policy : a critical discourse analysis of language attitudes in the United States of America

The narrative of the United States is of a "nation of immigrants" in which the language shift patterns of earlier ethnolinguistic groups have tended towards linguistic assimilation through English. In recent years, however, changes in the demographic landscape and language maintenance by non-English speaking immigrants, particularly Hispanics, have been perceived as threats and have led to calls for an official English language policy.This thesis aims to contribute to the study of language policy making from a societal security perspective as expressed in attitudes regarding language and identity originating in the daily interaction between language groups. The focus is on the role of language and American identity in relation to immigration. The study takes an interdisciplinary approach combining language policy studies, security theory, and critical discourse analysis. The material consists of articles collected from four newspapers, namely USA Today, The New York Times, Los Angeles Times, and San Francisco Chronicle between April 2006 and December 2007.Two discourse types are evident from the analysis namely Loyalty and Efficiency. The former is mainly marked by concerns of national identity and contains speech acts of security related to language shift, choice and English for unity. Immigrants are represented as dehumanised, and harmful. Immigration is given as sovereignty-related, racial, and as war. The discourse type of Efficiency is mainly instrumental and contains speech acts of security related to cost, provision of services, health and safety, and social mobility. Immigrants are further represented as a labour resource. These discourse types reflect how the construction of the linguistic 'we' is expected to be maintained. Loyalty is triggered by arguments that the collective identity is threatened and is itself used in reproducing the collective 'we' through hegemonic expressions of monolingualism in the public space and semi-public space. The denigration of immigrants is used as a tool for enhancing societal security through solidarity and as a possible justification for the denial of minority rights. Also, although language acquisition patterns still follow the historical trend of language shift, factors indicating cultural separateness such as the appearance of speech communities or the use of minority languages in the public space and semi-public space have led to manifestations of intolerance. Examples of discrimination and prejudice towards minority groups indicate that the perception of worth of a shared language differs from the actual worth of dominant language acquisition for integration purposes. The study further indicates that the efficient working of the free market by using minority languages to sell services or buy labour is perceived as conflicting with nation-building notions since it may create separately functioning sub-communities with a new cultural capital recognised as legitimate competence. The discourse types mainly represent securitising moves constructing existential threats. The perception of threat and ideas of national belonging are primarily based on a zero-sum notion favouring monolingualism. Further, the identity of the immigrant individual is seen as dynamic and adaptable to assimilationist measures whereas the identity of the state and its members are perceived as static. Also, the study shows that debates concerning language status are linked to extra-linguistic matters. To conclude, policy makers in the US need to consider the relationship between four factors, namely societal security based on collective identity, individual/human security, human rights, and a changing linguistic demography, for proposed language intervention measures to be successful.

Videography as production nexus : digital film cameras, media mangement and the distribution of creativity

This thesis is about new digital moving image recording technologies and how they augment the distribution of creativity and the flexibility in moving image production systems, but also impose constraints on how images flow through the production system. The central concept developed in this thesis is ‘creative space’ which links quality and efficiency in moving image production to time for creative work, capacity of digital tools, user skills and the constitution of digital moving image material. The empirical evidence of this thesis is primarily based on semi-structured interviews conducted with Swedish film and TV production representatives.This thesis highlights the importance of pre-production technical planning and proposes a design management support tool (MI-FLOW) as a way to leverage functional workflows that is a prerequisite for efficient and cost effective moving image production.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.