Suchergebnisse

This paper analyses the self-presentation of Barcelona Mayor Ada Colau in a period in which she had to consolidate her political identity as a result of her victory in the elections on May 25th 2015. Studying the Mayor's posts on her personal Facebook site during her first year and a half in office, we will analyse the configuration of Colau's discursive ethos. We will take into account five types of ethos we have identified in the corpus: that of activist, humanitarian, politician, mayor and leader. Based on the hypothesis that this ethos is extremely complex. We consider that her ethos is extremely complex due to the fact that it is based on various characteristics, which gives rise to a multi-form 'I' that fulfills Colau's need to legitimize her public image from a new position of power. ; Este trabajo propone analizar discursivamente la presentación de sí de la alcaldesa de Barcelona, Ada Colau, en un momento de afianzamiento de su identidad política disparado por su triunfo en las elecciones del 24 de mayo de 2015. A partir de un abordaje de las publicaciones de la alcaldesa en su página personal de Facebook durante el primer año y medio de su mandato, estudiaremos la construcción discursiva del ethos de Colau. Consideraremos cinco tipos de ethos que hemos identificado en el corpus: activista, humanidad, política, alcaldesa, líder. Sostenemos que su ethos es sumamente complejo en tanto radica en la conjunción de diferentes rasgos, dando lugar a un yo multiforme que responde a la necesidad de Colau de legitimar su imagen pública desde un nuevo lugar de poder.

The paper describes the application to longitudinal research of a method of data collection which combines quantitative and qualitative material. It is claimed that Group Feedback Analysis (GFA) helps to validate data collected by various methods and produces additional ethnographic material and insight into the process under investigation. When the people who supply the data are experienced in the subject matter, as is the case with managers and other employees in organizational research, GFA makes it possible for them to help with the interpretation of the data instead of leaving it entirely to the researcher. The method, which has previously been used in cross-sectional research, is shown to have utility in a longitudinal design where it can facilitate organizational learning. It can also contribute to the refinement of a theoretical model.

"Applied Multiway Data Analysis presents a unique, thorough, and authoritative treatment of this relatively new and emerging approach to data analysis that is applicable across a range of fields, from the social and behavioral sciences to agriculture, environmental sciences, and chemistry. General introductions to multiway data types, methods, and estimation procedures are provided in addition to detailed explanations and advice for readers who would like to learn more about applying multiway methods. Using carefully laid out examples and engaging applications, the book begins with an introductory chapter that serves as a general overview of multiway analysis, including the types of problems it can address. Next, the process of setting up, carrying out, and evaluating multiway analyses is discussed along with commonly-encountered issues, such as preprocessing, missing data, model and dimensionality selection, postprocessing, transformation, as well as robustness and stability issues"--Provided by publisher

The main purpose of this paper is to advocate a rule-based forecasting technique for anticipating stock index volatility. This paper intends to set up a stock index indicators projection prototype by using a multiple criteria decision making model consisting of the cluster analysis (CA) technique and Rough Set Theory (RST) to select the important attributes and forecast TSEC Capitalization Weighted Stock Index. The projection prototype was then released to forecast the stock index in the first half of 2009 with an accuracy of 66.67%. The results point out that the decision rules were authenticated to employ in forecasting the stock index volatility appropriately.

Benefit-cost analysis reduces all of the impacts of a proposed policy change to a common unit of measurement. It is used in a wide variety of fields including agriculture, life and health, transportation and the environment. In this single volume the editors, both leading scholars in their field, present a judicious selection of previously published papers indispensable to the study of applied benefit-cost analysis. The comprehensive collection is an essential resource to scholars, researchers and policymakers alike

"The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website includes datasets and analysis examples from the book, up-to-date software information, and other resources. Subject areas/Key words: advanced quantitative methods, management, survey, longitudinal, structural equation modeling, handling, how to handle, incomplete, multivariate, social research, behavioral sciences, statistical techniques, textbooks, seminars, doctoral courses, multiple imputation, models, MCAR, MNAR, Bayesian Audience: Researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science."--