"La leyenda tiene una base real" : Análisis crítico del discurso de un artículo de El País

This paper carries out a critical discourse analysis (CDA) of the article "¿Chinofobia?” published by the Spanish newspaper El País. It applies the theory of racist discourse in the media as formulated by Teun A. van Dijk. Its hypothesis is that the article, which supposedly analyses discrimination against the Chinese minority in Spain, covertly blames the Chinese minority itself for the discrimination. Applying CDA methodology as exemplified in previous studies by van Dijk, the paper analyses the article on global and local levels, and delineates its mental model. The global level analysis describes the article in terms of macropropositions and proposes a macrostructure: the self-alienation of the Chinese minority. The paper then analyses how the macrostructure is reinforced on the local level through micropropositions by examining 1) how vocabulary serves the negative presentation and othering of the Chinese minority, 2) how strategies of mitigation minimise discrimination by employing imprecise and vague language, 3) how quotes are used to give coherence and force to the macrostructure, 4) how implications associate the Chinese minority with criminality, and 5) how stereotyped beliefs about the Chinese minority are presented as common sense (presuppositions) and fallaciously argued. Finally, the paper delineates the mental model: the presuppositions about integration, and the implicit warning that minorities should integrate or they will be discriminated against.

Engineering tools

The aim of this report is to give an overview of the results of Work Package 5 “Engineering Tools”. In this workpackage numerical tools have been developed for all relevant CHCP systems in the PolySMART demonstration projects (WP3). First, existing simulation platforms have been described and specific characteristics have been identified. Several different simulation platforms are in principle appropriate for the needs in the PolySMART project. The result is an evaluation of available simulation and engineering tools for CHCP simulation, and an agreement upon a common simulation environment within the PolySMART project. Next, numerical models for components in the demonstration projects have been developed. These models are available to the PolySMART consortium. Of all modeled components an overall and detailed working principle is formulated, including a parameter list and (in some cases) a control strategy. Finally, for four CHCP systems in the PolySMART project, a system simulation model has been developed. For each system simulation a separate deliverable is available (D5.5b to D5.5e) These deliverables replace deliverable 5.4 ‘system models’. The numerical models for components and systems developed in the Polysmart project form a valuable basis for the component development and optimisation and for the system optimisation, both within and outside the project. Developers and researchers interested in more information about specific models can refer to the institutes and contact persons involved in the model development. 

Increasing the power of genome wide association studies in natural populations using repeated measures : evaluation and implementation

1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

Shared decision-making in mental health care : a user perspective on decisional needs in community-based services

BACKGROUND: Shared decision-making (SDM) is an emergent research topic in the field of mental health care and is considered to be a central component of a recovery-oriented system. Despite the evidence suggesting the benefits of this change in the power relationship between users and practitioners, the method has not been widely implemented in clinical practice. OBJECTIVE: The objective of this study was to investigate decisional and information needs among users with mental illness as a prerequisite for the development of a decision support tool aimed at supporting SDM in community-based mental health services in Sweden. METHODS: Three semi-structured focus group interviews were conducted with 22 adult users with mental illness. The transcribed interviews were analyzed using a directed content analysis. This method was used to develop an in-depth understanding of the decisional process as well as to validate and conceptually extend Elwyn et al.'s model of SDM. RESULTS: The model Elwyn et al. have created for SDM in somatic care fits well for mental health services, both in terms of process and content. However, the results also suggest an extension of the model because decisions related to mental illness are often complex and involve a number of life domains. Issues related to social context and individual recovery point to the need for a preparation phase focused on establishing cooperation and mutual understanding as well as a clear follow-up phase that allows for feedback and adjustments to the decision-making process. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: The current study contributes to a deeper understanding of decisional and information needs among users of community-based mental health services that may reduce barriers to participation in decision-making. The results also shed light on attitudinal, relationship-based, and cognitive factors that are important to consider in adapting SDM in the mental health system.