Validation of a measurement scale for the relationship between the orientation to corporate social responsibility and other business strategic variables

The importance of Social Responsibility (SR) is higher if this business variable is related with other ones of strategic nature in business activity (competitive success that the company achieved, performance that the firms develop and innovations that they carries out). The hypothesis is that organizations that focus on SR are those who get higher outputs and innovate more, achieving greater competitive success. A scale for measuring the orientation to SR has defined in order to determine the degree of relationship between above elements. This instrument is original because previous scales do not exist in the literature which could measure, on the one hand, the three classics sub-constructs theoretically accepted that SR is made up and, on the other hand, the relationship between SR and the other variables. As a result of causal relationships analysis we conclude with a scale of 21 indicators, validated scale with a sample of firms belonging to the Autonomous Community of Extremadura and it is the first empirical validation of these dimensions we know so far, in this context.

Cidadania e diversidade em saúde: necessidades e estratégias de promoção de equidade nos cuidados

Este artigo introduz o conceito de cidadania associado à sua concretização no âmbito da saúde em contextos de diversidade. Conjuga resultados de vários projetos de investigação de cariz qualitativo como forma de ilustrar algumas das estratégias concebidas pelo Estado e pela sociedade civil em resposta às mudanças trazidas pelas migrações internacionais. Assim, identificam-se as necessidades da população, as barreiras de acesso aos cuidados de saúde, as principais fontes de desigualdades e iniquidade e algumas das estratégias desenvolvidas na promoção da equidade em saúde, alertando para a importância de levar em consideração as questões culturais e as de índole socioeconómica.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.