Sources of Bias and Quality of Data in Social Science Research

2002 ◽  
Author(s):  
Andreas Diekmann
2018 ◽  
Author(s):  
Mercè Crosas ◽  
Julian Gautier ◽  
Sebastian Karcher ◽  
Dessi Kirilova ◽  
Gerard Otalora ◽  
...  

By encouraging and requiring that authors share their data in order to publish articles, scholarly journals have become an important actor in the movement to improve the openness of data and the reproducibility of research. But how many social science journals encourage or mandate that authors share the data supporting their research findings? How does the share of journal data policies vary by discipline? What influences these journals’ decisions to adopt such policies and instructions? And what do those policies and instructions look like?We discuss the results of our analysis of the instructions and policies of 291 highly-ranked journals publishing social science research, where we studied the contents of journal data policies and instructions across 14 variables, such as when and how authors are asked to share their data, and what role journal ranking and age play in the existence and quality of data policies and instructions. We also compare our results to the results of other studies that have analyzed the policies of social science journals, although differences in the journals chosen and how each study defines what constitutes a data policy limit this comparison.We conclude that a little more than half of the journals in our study have data policies. A greater share of the economics journals have data policies and mandate sharing, followed by political science/international relations and psychology journals.Finally, we use our findings to make several recommendations: Policies should include the terms “data,” “dataset” or more specific terms that make it clear what to make available; policies should include the benefits of data sharing; journals, publishers, and associations need to collaborate more to clarify data policies; and policies should explicitly ask for qualitative data.


Author(s):  
Mats Alvesson ◽  
Yiannis Gabriel ◽  
Roland Paulsen

This book argues that we are currently witnessing not merely a decline in the quality of social science research, but a proliferation of meaningless research of no value to society and modest value to its authors—apart from securing employment and promotion. The explosion of published outputs, at least in social science, creates a noisy, cluttered environment which makes meaningful research difficult, as different voices compete to capture the limelight even briefly. Older, but more impressive contributions are easily neglected as the premium is to write and publish, not read and learn. The result is a widespread cynicism among academics on the value of academic research, sometimes including their own. Publishing comes to be seen as a game of hits and misses, devoid of intrinsic meaning and value and of no wider social uses whatsoever. This is what the book views as the rise of nonsense in academic research, which represents a serious social problem. It undermines the very point of social science. This problem is far from ‘academic’. It affects many areas of social and political life entailing extensive waste of resources and inflated student fees as well as costs to taxpayers. The book’s second part offers a range of proposals aimed at restoring meaning at the heart of social science research, and drawing social science back, address the major problems and issues that face our societies.


2021 ◽  
pp. 107554702110188
Author(s):  
Jennifer Shannon ◽  
Claire Quimby ◽  
Chip Colwell ◽  
Scott Burg

This is a call to science communicators and science journalists to feature social science research and researchers in their reporting, with an emphasis on anthropology and its potential to increase public empathy, improve the quality of public discourse, and contribute to contextual and narrative news trends.


Author(s):  
Nicholas Charron

This chapter discusses a wide scope of the available indicators of quality of government. It begins with a brief history of the development of the indicators and their scientific impact on social science research. The chapter posits a typology of the various ways in which indicators of governance can differ and implications of such differences. The chapter then reveals the degree to which contemporary cross-country indicators of corruption in particular correlate. Next, several well-established critiques of contemporary data are presented. The chapter concludes with several comments on what makes a good quality indicator and puts for several suggestions for future work in this ever-growing field.


2019 ◽  
Vol 95 ◽  
pp. 1-17 ◽  
Author(s):  
Jacob Doherty ◽  
Kate Brown

AbstractWaste studies brings to labor history a suite of conceptual tools to think about precarious labor, human capital, migration, the material quality of labor in urban and rural infrastructures, and the porosity and interchangeability of workers’ bodies in the toxic environments in which they labor. In this introduction, we explore the conceptual insights that the study of waste offers for the field of labor history, and what, in turn, a focus on labor history affords to social science research on waste. We examine the relationship between surplus populations and surplus materials, the location of waste work at the ambiguous fulcrum of trash and value, and the significance of labor for the understanding of infrastructure.


Social science research (SSR) has a vital role in enriching societies, by generating scientific knowledge that brings insights—even enlightenment—in understanding the dynamics of human behaviour and development. For social sciences to realize their potential in shaping public policy, it is imperative that the research ecosystem is dynamic and vibrant; the institutions governing it are robust and effective; and those producing quality research are strong and well governed. This volume elaborates on various dimensions of SSR in India, presenting a strong case for designing a comprehensive national social science policy which can meaningfully strengthen and promote a research ecosystem for improved public policymaking in the country. Addressing issues like lack of funding, availability of data, infrastructure, and quality of research output, it will serve as a national benchmark and reference database for social sciences in India.


Author(s):  
Amit Shovon Ray ◽  
M. Parameswaran ◽  
Manmohan Agarwal ◽  
Sunandan Ghosh ◽  
Udaya S. Mishra ◽  
...  

The chapter analyses the quality of research in terms of quality of articles and of journals by using a quality index. It uses two-dimension indicators to judge the quality of articles, that is, citations (scholarly) and readership, which is the number of hits an article receives in a simple Google keyword search. The quality of a journal is measured in terms of three dimensions: its presence over time, its presence across space, and its depth. The study took 21351 journal articles from 1006 journals (902 journals from Scopus and 104 journals from ISID for five-year period, 2010–14. It emerged that India’s social science research (SSR) contributes more to public debates and policy formulations and relatively less in pushing the frontiers of knowledge for further research.


Author(s):  
Gordon C.C. Douglas

Chapter 4 focuses on the personal and professional background of many do-it-yourselfers who employ sophisticated knowledge of professional planning and scholarly urbanism in their interventions. In doing so, it begins to challenge binary notions of formality and informality in urbanism. The chapter includes discussion of the history of informality in cities and the development of professionalized urban planning and placemaking practices. It then discusses how many do-it-yourself urban designers have professional design training that they to use in their projects. Where others lack such a background, they often seek information from official sources in order to strengthen and legitimate their interventions, from tools, techniques, and guidelines to justifications grounded in social science research. Although this may lead to better-designed and more effective improvements, it also gives the individuals a certain confidence in the quality of their actions and their right to make them.


2017 ◽  
Vol 7 (1&2) ◽  
Author(s):  
Jia Li Huang

Since the 1990s, many education researchers and policy makers worldwide have reviewed education research to attempt to provide strategies to improve the quality of such research in their countries. Taiwan’s government has launched policies and funded support to set the benchmark for Taiwan’s leading universities in international academic competition. The external environment of global competition based on research policy influences the ecosystem of social science research production. To assure the quality of education policy, peer review from within the education community is one approach to supplementing the government’s governance, including the establishment of research institutes, promotion, rewards, and research value. This study tracked the mode of academic research and provides an overview of the status of academic education research in Taiwan. Because education research is part of the humanities and social sciences fields, this study identified the challenges in educational research by examining the trend of social science research and by analyzing research organizations, policy, and the evaluation of research performance. Due to the environment of education research in Taiwan is not friendly to education researcher to accumulate papers in SSCI or international journal, additional concerns entail how education research communities can develop and agree on its quality.


2020 ◽  
Vol 122 (11) ◽  
pp. 1-38
Author(s):  
Sean Kelly ◽  
Zachary Mozenter ◽  
Esteban Aucejo ◽  
Jane Cooley Fruehwirth

Background/Context There is continuing debate among social scientists and educators about the role of school-to-school differences in generating educational inequality. Are some students high achieving because they attend School A, while others struggle because they attend School B, as critical discourse on schools argues? Alternatively, is educational inequality driven largely by social forces outside of the school, in the home and neighborhood environment, or by educational processes that are largely common across schools as much social science research argues? Analyses of school achievement, and in particular test score gains from year-to-year, suggest very small between-school differences. Yet, analyses of test score data alone may fail to reveal important school-to-school differences that affect the quality of the classroom experience and a variety of educational outcomes. Purpose/Objective We provide evidence on the following research questions. What is the magnitude of school-to-school variation in instructional practice, as captured by multiple measures? Are some domains of instruction (e.g., behavioral management) more variable between schools than others? To what extent are school-to-school differences in instruction associated with compositional characteristics of students and teachers? Research Design This study relies on the Measures of Effective Teaching Study data, which offer an unprecedented set of observations of teachers’ instruction scored on state-of-the-art observational protocols. To examine the extent of school-to-school variation in instructional practice in elementary and middle schools, we conducted a decomposition of variance analysis using summary scores on multiple measures. We further examine behavioral climate as revealed during instruction separately from overall instructional practice. Next, we examine differences in instruction associated with compositional characteristics of students using multilevel models. Finally, we use an innovative two-stage statistical adjustment strategy to more narrowly identify the possible association between composition and teaching practice due to school-to-school teacher sorting. Findings/Results The basic descriptive results from this study suggest a middle view of school-to-school differences in instruction. We find that substantial school-level variation in instruction exists, with 30% or more of the total variance in instruction lying between schools in these data. Behavioral climate during instruction appears to be particularly salient, and especially in elementary schools. Much of the between school variance we identify, in some cases 40% or more, is readily explained by simple measures of socio-demographic composition, including in particular the racial make-up of schools in the MET districts. Finally, some evidence from a statistical adjustment method suggests that teacher sorting, rather than measurement bias and teacher adaptation, is principally responsible for school-to-school differences in instruction. Conclusions/Recommendations More than an academic debate, basic differences between schools in the quality of the learning environment, along with parental understandings and beliefs about school effects, are potentially important drivers of school and neighborhood sorting and segregation, and even public investment in schooling. Additionally, this question carries continued policy relevance as states adopt and revise teacher and school accountability frameworks that implicitly attribute school-to-school differences to organizational functioning, and seek to carry out instructional improvement efforts in targeted schools. The basic descriptive results from this study suggest school-level differences are not as great as suggested by critical theory and the public discourse, but neither are they as inconsequential as one might infer from some social science research or the literature on value-added differences between schools.


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