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The social sciences are becoming datafied. The questions once considered the domain of sociologists are now answered by data scientists operating on large datasets and breaking with methodological tradition, for better or worse. The traditional social sciences, such as sociology or anthropology, are under the double threat of becoming marginalised or even irrelevant, both from new methods of research which require more computational skills and from increasing competition from the corporate world which gains an additional advantage based on data access. However, unlike data scientists, sociologists and anthropologists have a long history of doing qualitative research. The more quantified datasets we have, the more difficult it is to interpret them without adding layers of qualitative interpretation. Big Data therefore needs Thick Data.

"Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure; Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure; Details SPSS paths for conducting various analyses; Discusses the interpretations of statistical results and conclusions of the research. With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output."--Publisher's website

Les sciences sociales entrent résolument – quoique partiellement – dans l'ère computationnelle. Ce constat n'a pas encore de sens précis si on ne l'accompagne d'une analyse discriminante des fonctions épistémiques de la computation dans les différents recours aux ordinateurs pour la modélisation et la simulation en sciences sociales. De par l'introduction de ces nouvelles manières de formaliser (séduisantes car apparaissant comme plus directes et plus ergonomiques), la double question du réalisme des formalismes et de la valeur de preuve des traitements computationnels se pose à nouveaux frais. Cette expansion tous azimuts des simulations computationnelles conduit certains observateurs enthousiastes à penser que l'on a là un nouveau fondement commun pour toutes les sciences sociales. En clarifiant et en distinguant certains des usages épistémiques de différentes simulations computationnelles dans les sciences sociales, cet article montre cependant qu'il vaut mieux s'en tenir à une position médiane et soutenir que l'apport en est principalement méthodologique.

Academic Days of Timisoara: Social Sciences Today is a book of the proceedings of the 3rd International Symposium "Social Sciences Today: Between Theory and Practice" held in Timisoara, Romania, on May 6-7, 2011, under the auspices of the Romanian Academy. It will appeal to teachers of social sciences, no matter the level of instruction. The papers it contains deal Other economics (economic crisis, communications, and Total Quality Management), education (systems of formal education, process o

The social sciences were latecomers to academia, and have only recently become sufficiently well-developed to fragment. The process began at the turn of the century. As each field became recognized scientific discipline, specialization furthered the growth of knowledge. (SJO)