Causality as validity: some implications for the social sciences

We analyse the concept of causality in the social sciences, whose development is insufficient and lesser than the methodology developed for its study. The nature of the causal process as the production of effects remains unclear and the relationships considered to be manifestations of that process cannot be taken for proof of its existence. Given these difficulties, we suggest that, aside from the inherited interpretations, the practice of the concept of causality makes reference to correctly specified relationships not confounded by others; characteristics identical to those which define validity. In that way, causality is equivalent to the validity of a relationship. Beyond merely re-understanding causality, this proposal permits the deduction that the temporal precedence of the cause is a necessary condition only for one type of causality, making it possible to consider other types, not admitted by the traditional notion, in which the cause is consequent or simultaneous to the variable to be explained. Examples and characteristics of these types of causality are presented and considered to be useful for the social sciences.     

Introducing dimensional analysis to the social sciences

This study serves to introduce dimensional analysis to the social sciences. Dimensional analysis, a method fundamental to research in the physical sciences, is presented first in a conceptual framework. Questions such as: what makes the method work, what use is it, and what are its limitations … are dealt with summarily. The method is then applied to the modeling of interurban migration. The selection of independent variables, the synthesis of dimensionless groups, and the analysis of data are considered in some detail.While a blanket endorsement of the method must be withheld pending further research, results of the present study are encouraging. Dimensional analysis may eventually find wide application in the social sciences.     

Modeling the act of measurement in the social sciences

Motivated by time-series experimental designs, we develop a model of the act of measurement in the social sciences. Meaningful measurements are represented by operators that obey a non-commutative algebra. Thus, the order in which information is extracted matters. In addition, responses to questions about an attribute depend on whether information about another attribute has previously been extracted. Measurement “forces” the subject to obtain one value of the attribute, the one measured by the observer. An uncertainty principle imposes a fundamental limit on the ability to extract detailed information about two distinct attributes within a short period of time.     

Computer assisted text analysis in the social sciences

We use the term “Computer Assisted Text Analysis” in a broad sense to refer to a range of current techniques from quantitative social science and content analysis to ‘data mining’ and ‘text classification’, including the analysis of open-ended survey questions, transcribed interviews and speeches, wherever, in fact, the researcher is confronted with data in the form of natural language texts of social scientific interest. These methods are often used in exploratory data analysis, but can also be applied systematically with moderate statistical rigour in the development and testing of hypotheses at various theoretical levels, ranging from the statistics of word usage to changes within or between discourses over time. The general approach is in the tradition of content analysis, by which words which occur together in relatively close proximity in the same context are interpreted as relating to a common theme or concept in the discourse studied. We review a comprehensive set of tools to identify and visualize structures of co-occurrence of words and concepts both within, and in comparing, a number of texts. These produce results not essentially different from those reached by representing word co-occurrences in terms of network analysis or neural network programming using schematic linguistic templates of various kinds. A comparison of the relational data analysis vs. a dictionary-based MDS approach shows that these provide very close if not identical results, despite the fact that the underlying assumptions are frequently represented as different theoretical approaches.     

The use of quasi-experiments in the social sciences: a content analysis

This article examines the use of various research designs in the social sciences as well as the choices that are made when a quasi-experimental design is used. A content analysis was carried out on articles published in 18 social science journals with various impact factors. The presence of quasi-experimental studies was investigated as well as choices in the design and analysis stage. It was found that quasi-experimental designs are not very often used in the inspected journals, and when they are applied they are not very well designed and analyzed. These findings suggest that the literature on how to deal with selection bias has not yet found its way to the practice of the applied researcher.     

High-frequency words have higher frequencies in Turkish social sciences article

Quality & Quantity - Words, sentences, and paragraphs are the basis of texts. When we consider texts as data and want to establish a relationship between qualitative and quantitative...     

Software as a facilitator of quality processes in social sciences research

The objective of this work is to evaluate the strategy of triangulation in the validation of information by integrating quantitative/qualitative information based on the use of different statistics software packages In our case, we opted to begin with a quantitative strategy and use IBM SPSS AMOS Statistics; we then replicated the study with a qualitative strategy using NVIVO. To this end, we used as an example case a study conducted on a sample of 445 university teaching personnel regarding intentions to use the blended learning teaching model in their usual teaching practice. We did so to analyse the extent to which it is possible to explain the process of adopting this educational method as well as its use and its dissemination in higher-education contexts, taking as a theoretical reference the Unified Theory of Acceptance and Use of Technology and the Theory of Diffusion of Innovation, proposed by E. Rogers. The analyses carried out verified the convergence or overlap of the results obtained after the application of different methods of data collection (a questionnaire and interviews) for the same study object. The results confirm the benefit of using data-processing software as a resource to facilitate multimethod strategies in educational research owing to its strengthening of results and the examination of the level of convergence or divergences within them.     

Testing for short- and long-run causality: A frequency-domain approach

The framework of Geweke (1982. Journal of the American Statistical Association 77, 304–324.) and Hosoya (1991. Probability Theory and Related Fields 88, 429–444.) is adopted to construct a simple test for causality in the frequency domain. This test can also be applied to cointegrated systems. To study the large sample properties of the test, we analyze the power against a sequence of local alternatives. The finite sample properties are investigated by means of Monte Carlo simulations. Our methodology is applied to investigate the predictive content of the yield spread for future output growth. Using quarterly US data we observe reasonable leading indicator properties at frequencies around one year and typical business cycle frequencies.     

Action embedded in social structure: A systematic theory Part I,theory and evidence

This research develops a systematic theory, which premises a responsible and reasonable actor, of how social structure can affect rational social action, applies this general theory to explain 29 specific empirical findings about voting, and illustrates how deductive theories can synthesize prior empirical findings and provide a focus for subsequent empirical research. Part II, Explanations applies the systematic theory to account for specific empirical propositions that relate social statuses to the decisions voters make. Voters are classified by such graduated social statuses as socioeconomic class, age, and education; and by such nominal social statuses as religion, urban or rural residence, region, gender, race, and ethnicity. Positions on two key issues affect voting choice, the desire for economic equity and the desire for social equality. The members of the various social groups interpret these issues as they affect their own self-interest, and align with the party they perceive as furthering their interests. To corroborate aspects of the theory and to quantify the effects of the variables, survey data are analyzed.     

Publication bias in the German social sciences: an application of the caliper test to three top-tier German social science journals

Systematic research reviews have become essential in all empirical sciences. However, the validity of research syntheses is threatened if the preparation, submission or publication of research findings depends on the statistical significance of these findings. The present study investigates publication bias in three top-tier journals in the German social sciences, utilizing the caliper test. For the period between 2001 and 2010, we have collected 156 articles that appeared in the Kölner Zeitschrift für Soziologie und Sozialpsychologie (KZfSS), the Zeitschrift für Soziologie (ZfS) and the Politische Vierteljahresschrift (PVS). In all three journals, we found empirical evidence for the existence of publication bias at the 10 % significance level. We also investigated possible causes linked to this bias, including single versus multiple authorship as well as academic degree. We found only weak support for the relationships between individual author characteristics and publication bias.     

The characterization of instantaneous causality: A correction

The purpose of this paper is to show that it is not possible to determine whether instantaneous causality exists between two time series by examining their contemporaneous cross-correlation.