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.

Self-reported symptoms and motor tests via telemetry in a 36-month levodopa-carbidopa intestinal gel infusion trial

Objective To investigate if a home environment test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression. Background Seventy-seven patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study at 10 clinics in Sweden and Norway; 40 of them were treated with levodopa-carbidopa intestinal gel (LCIG) and 37 patients were candidates for switching from oral PD treatment to LCIG. They utilized a mobile device test battery, consisting of self-assessments of symptoms and objective measures of motor function through a set of fine motor tests (tapping and spiral drawings), in their homes. Both the LCIG-naïve and LCIG-non-naïve patients used the test battery four times per day during week-long test periods. Methods Assessments The LCIG-naïve patients used the test battery at baseline (before LCIG), month 0 (first visit; at least 3 months after intraduodenal LCIG), and thereafter quarterly for the first year and biannually for the second and third years. The LCIG-non-naïve patients used the test battery from the first visit, i.e. month 0. Out of the 77 patients, only 65 utilized the test battery; 35 were LCIG-non-naïve and 30 LCIG-naïve. In 20 of the LCIG-naïve patients, assessments with the test battery were available during oral treatment and at least one test period after having started infusion treatment. Three LCIG-naïve patients did not use the test battery at baseline but had at least one test period of assessments thereafter. Hence, n=23 in the LCIG-naïve group. In total, symptom assessments in the full sample (including both patient groups) were collected during 379 test periods and 10079 test occasions. For 369 of these test periods, clinical assessments including UPDRS and PDQ-39 were performed in afternoons at the start of the test periods. The repeated measurements of the test battery were processed and summarized into scores representing patients’ symptom severities over a test period, using statistical methods. Six conceptual dimensions were defined; four subjectively-reported: ‘walking’, ‘satisfied’, ‘dyskinesia’, and ‘off’ and two objectively-measured: ‘tapping’ and ‘spiral’. In addition, an ‘overall test score’ (OTS) was defined to represent the global health condition of the patient during a test period. Statistical methods Change in the test battery scores over time, that is at baseline and follow-up test periods, was assessed with linear mixed-effects models with patient ID as a random effect and test period as a fixed effect of interest. The within-patient variability of OTS was assessed using intra-class correlation coefficient (ICC), for the two patient groups. Correlations between clinical rating scores and test battery scores were assessed using Spearman’s rank correlations (rho). Results In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. However, there were no significant changes in mean OTS scores of LCIG-non-naïve patients, except for worse mean OTS at month 36 (p<0.01, n=16). The mean scores of all subjectively-reported dimensions improved significantly throughout the course of the study, except ‘walking’ at month 36 (p=0.41, n=4). However, there were no significant differences in mean scores of objectively-measured dimensions between baseline and other test periods, except improved ‘tapping’ at month 6 and month 36, and ‘spiral’ at month 3 (p<0.05). The LCIG-naïve patients had a higher within-subject variability in their OTS scores (ICC=0.67) compared to LCIG-non-naïve patients (ICC=0.71). The OTS correlated adequately with total UPDRS (rho=0.59) and total PDQ-39 (rho=0.59). Conclusions In this 3-year follow-up study of advanced PD patients treated with LCIG we found that it is possible to monitor PD progression over time using a home environment test battery. The significant improvements in the mean OTS scores indicate that the test battery is able to measure functional improvement with LCIG sustained over at least 24 months.

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.

Machine Learning Algorithms in Heavy Process Manufacturing

In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.