Infrastructure for Survey Data Processing in Urban and Planning Studies

2012 ◽  
pp. 17-36
Author(s):  
Randall J. Olsen
Keyword(s):  
Survey Data ◽  
Relational Databases ◽  
Social Science Research ◽  
Science Research ◽  
Detailed Data ◽  
New Paradigm ◽  
Social Phenomena ◽  
Web Based ◽  
Quarter Century ◽  
Applied Social Science

Applied social science research has increasingly come to rely on surveys to generate detailed data, especially on firms, persons, and households, needed to study social phenomena. The methods used to collect survey data have changed substantially in the past quarter century and appear on the cusp of changing again with the rise of Web-based technologies. These changes can be best implemented by adopting computational methods designed for relational databases. This is true not only for survey data, but also administrative data that government agencies collect, store, and use. In this chapter, the author explains how these changes are best accommodated and how new telecommunications technologies, including Voice over Internet and smart phones, fit into this new paradigm. These techniques dominate survey data collection for urban studies and other fields.

Bottom-Up and Top-Down Approaches to Simulate Complex Social Phenomena

2018 ◽  
Vol 9 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Ahmed M'hamdi ◽  
Mohamed Nemiche
Keyword(s):  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Social Simulation ◽  
New Paradigm ◽  
Top Down ◽  
Social Phenomena ◽  
Virtual Laboratories ◽  
Model Complex ◽  
Linear Interactions

Social science research is concerned with the study of processes and phenomena in human societies, institutions and organizations. Social phenomena are complex due to many non-linear interactions between their elements. Social simulation represents a new paradigm for understanding social complexity with approaches that use advanced computational capabilities. The success of social simulation is largely due to its capability to test and validate hypotheses of social phenomena by the construction of virtual laboratories. This paper provides an introduction to social simulation and discusses approaches to model complex social phenomena.

scholarly journals Is Banning Significance Testing the Best Way to Improve Applied Social Science Research? – Questions on

2016 ◽  
Vol 21 (3) ◽  
pp. 95-105
Author(s):  
Thees F Spreckelsen ◽  
Mariska Van Der Horst
Keyword(s):  
Social Science ◽  
Statistical Significance ◽  
Social Science Research ◽  
Science Research ◽  
Research Process ◽  
Significance Testing ◽  
Sociological Research ◽  
Research Practice ◽  
Research Questions ◽  
Applied Social Science

Significance testing is widely used in social science research. It has long been criticised on statistical grounds and problems in the research practice. This paper is an applied researchers’ response to Gorard's (2016) ‘Damaging real lives through obstinacy: re-emphasising why significance testing is wrong’ in Sociological Research Online 21(1). He participates in this debate concluding from the issues raised that the use and teaching of significance testing should cease immediately. In that, he goes beyond a mere ban of significance testing, but claims that researchers still doing this are being unethical. We argue that his attack on applied scientists is unlikely to improve social science research and we believe he does not sufficiently prove his claims. In particular we are concerned that with a narrow focus on statistical significance, Gorard misses alternative, if not more important, explanations for the often-lamented problems in social science research. Instead, we argue that it is important to take into account the full research process, not just the step of data analysis, to get a better idea of the best evidence regarding a hypothesis.

Visitor Studies in a Political World: Challenges to Evaluation Research

2002 ◽  
Vol 7 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Ross J. Loomis
Keyword(s):  
Process Model ◽  
Evaluation Research ◽  
Social Science Research ◽  
Evaluation Process ◽  
Science Research ◽  
Visitor Studies ◽  
Political Factors ◽  
Routine Work ◽  
Applied Social Science

The evaluation process model consisting of front-end, formative, and summative studies has received fairly wide acceptance among professionals in various kinds of interpretation work. Evaluation can be used throughout the development of exhibits and programs. This acceptance, however, is not as widespread as might be desirable. While some professionals in interpretive settings accept evaluation and incorporate it into routine work, others do not. Misunderstanding about the role of applied social science research is one source of resistance. Misunderstandings can focus around purposes for evaluation, the real world context of applied research, and methods of study. Other barriers include differences in decision-making philosophy, such as the value put on intuitive judgment versus use of rational data-based decisions. A number of political factors can inhibit use of evaluation, including fear of findings that are critical of interpretive work. Fortunately, there are some ways being developed for coping with resistance to evaluation.

scholarly journals Analyzing factorial survey data with structural equation models

2021 ◽  
pp. 004912412110431
Author(s):  
Bert Weijters ◽  
Eldad Davidov ◽  
Hans Baumgartner
Keyword(s):  
Structural Equation Modeling ◽  
Survey Data ◽  
Structural Equation ◽  
Multilevel Models ◽  
Structural Equation Models ◽  
Social Science Research ◽  
Science Research ◽  
Equation Modeling ◽  
Factorial Survey ◽  
Modeling Framework

In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.

Sociodrama for Training Applied Anthropologists

1987 ◽  
Vol 9 (2) ◽  
pp. 13-16
Author(s):  
David Rymph
Keyword(s):  
Social Science ◽  
Graduate Training ◽  
Evaluation Research ◽  
Social Science Research ◽  
Science Research ◽  
Health Department ◽  
Practical Experience ◽  
Lessons Learned ◽  
Applied Social Science ◽  
Fayette County

As a practicing anthropologist with strong ties to university-based graduate training programs, I have occasionally been invited to give guest lectures to classes in applied anthropology, evaluation research, and public administration. When asked to share my practical experience, what I have most often wanted to communicate to students are the lessons learned on the job about how administrators, program people, and researchers get on with one another. I am referring to my own struggles to learn and adapt to the social realities of how public agencies make decisions about the proper use of social science research. While lectures on behavior in complex organizations may be helpful, experience is the better teacher. Toward this end, my colleague Carol Bryant, a Ph.D. anthropologist with the Lexington-Fayette County, Kentucky Health Department, and I have developed a technique to help trainees experience the multi dimensional character of applied social science problems in human service systems. Combining role play with conflict resolution goals, sociodrama gives students and trainees the opportunity to act out aspects of real world roles and problem situations in a non-threatening and supportive atmosphere.

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