Imperatives for Theories in Social Science: The North-South Divide Notwithstanding

2020 ◽  
Vol 19 (3) ◽  
pp. 195-217
Author(s):  
Aaron Ola Ogundiwin, ◽  
Joel N. Nwachukwu

Abstract The paper underscores the place of theories in organizing social science data and experience. It holds that theories are indispensable to social research (The North-South divide notwithstanding), in view of the fact that the framework of knowledge and experience within which theories are established make a meaningful explanation of the world phenomenon reasonably possible. It delineates political philosophy and history of ideas from theory and thus, takes care of common mistake social scientists make differentiating between them. Furthermore, the paper on one hand, takes on the scientific requisites of theory such as assumption, concepts (and their functions), hypothesis (and its characteristics typology), law, models, paradigm and provides lucid conceptual analysis of each with a view to showing their relatedness to theory but not as synonyms to it. On the other hand, we singled out dependency theory in its emanation from knowledge and experience of underdevelopment of Third World countries, as the first and perhaps most relevant theoretic explanation of Africa’s underdevelopment. The paper posits that a good theory that will serve as a rudder for formulation of research questions, problem statement, as well as sustain the data analysis, and findings must parade some, if not all of the following qualities: precision and testability, empirical validity, parsimony, stimulation, and practicability.

2019 ◽  
Vol 15 (1) ◽  
pp. 72-91
Author(s):  
Kerstin Brückweh ◽  
Kathrin Zöller

In recent years, historians have increasingly looked at social science data in their search for sources to study the transformation period. Researchers hope that a secondary analysis of this data will expand the existing sources. This expansion promises new perspectives, while simultaneously bringing new methodological challenges to the discipline. This article deals with both: 1. It uses a history of knowledge approach to evaluate the topics and tools of transformation research. It also argues that social scientists were not only producers of knowledge but historical actors in the restructuring of the institutions of social sciences in East Germany after 1989/90. 2. With the German Socio-Economic Panel and especially the Saxonian Longitudinal Study as an example, the article refers to the content of the studies itself – in this case, the East German school as a site of life-worlds in upheaval. It concludes that the encounter of social scientists and historians is very fruitful for historians interested in the interaction of system change and everyday life. That is, the secondary analysis of qualitative and quantitative social science data compliments ‘classical’ sources of historical research by providing insights into memories and experiences at different times in the historical process.


Author(s):  
Laine Ruus

Traditional quantitative social science data analysis requires three ingredients: the raw data, metadata (what we used to call a codebook), and software. Software changes all the time, within some limits. Raw data without metadata is useless: it might as well be generated by a random number generator. And metadata without data is like the index to a periodical the last remaining copy of which was sent for recycling last month. Over time, metadata have been expected to support many different functions, and microsolutions have never quite satisfied many, much less all, of those functions. Until recently, that is: a roughly 25-year process of historical evolution has led to DDI, the Data Documentation Initiative, which unites several levels of metadata in one emerging standard.


1997 ◽  
Vol 17 (3) ◽  
pp. 323-335 ◽  
Author(s):  
GEORGE L. MADDOX

A revolution is occurring in information exchange among gerontologists worldwide. For research investigators the increasingly easy accessibility of public use datasets promises to facilitate both research training and useful exchange of evidence. A brief history of the development of public use datasets for research in ageing is provided, and datasets of particular interest are described. While the illustrations focus on experience in the United States the implications of these developments for training and communication among gerontologists worldwide are noted.


Author(s):  
Matthew Brook O’Donnell ◽  
Emily B. Falk

Methods for analyzing neural and computational social science data are usually used by different types of scientists and generally seen as distinct, but they strongly complement one another. Computational social science methodologies can strengthen and contextualize individual-level analysis, specifically our understanding of the brain. Neuroscience can help to unpack the mechanisms that lead from micro- through meso- to macro-level observations. Integrating levels of analysis is essential to unified progress in social research. We present two example areas that illustrate this integration. First, combining egocentric social network data with neural variables from the “egos” provides insight about why and for whom certain types of antismoking messages may be more or less effective. Second, combining tools from natural language processing with neuroimaging reveals mechanisms involved in successful message propagation, and suggests links from microscopic to macroscopic scales.


2020 ◽  
Vol 33 (2) ◽  
pp. 101-119
Author(s):  
Emily Hauptmann

ArgumentMost social scientists today think of data sharing as an ethical imperative essential to making social science more transparent, verifiable, and replicable. But what moved the architects of some of the U.S.’s first university-based social scientific research institutions, the University of Michigan’s Institute for Social Research (ISR), and its spin-off, the Inter-university Consortium for Political and Social Research (ICPSR), to share their data? Relying primarily on archived records, unpublished personal papers, and oral histories, I show that Angus Campbell, Warren Miller, Philip Converse, and others understood sharing data not as an ethical imperative intrinsic to social science but as a useful means to the diverse ends of financial stability, scholarly and institutional autonomy, and epistemological reproduction. I conclude that data sharing must be evaluated not only on the basis of the scientific ideals its supporters affirm, but also on the professional objectives it serves.


1976 ◽  
Vol 5 (5) ◽  
pp. 11-13
Author(s):  
PATRICIA E. STIVERS

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