scholarly journals Big data and Belmont: On the ethics and research implications of consumer-based datasets

2021 ◽  
Vol 8 (2) ◽  
pp. 205395172110481
Author(s):  
Remy Stewart

Consumer-based datasets are the products of data brokerage firms that agglomerate millions of personal records on the adult US population. This big data commodity is purchased by both companies and individual clients for purposes such as marketing, risk prevention, and identity searches. The sheer magnitude and population coverage of available consumer-based datasets and the opacity of the business practices that create these datasets pose emergent ethical challenges within the computational social sciences that have begun to incorporate consumer-based datasets into empirical research. To directly engage with the core ethical debates around the use of consumer-based datasets within social science research, I first consider two case study applications of consumer-based dataset-based scholarship. I then focus on three primary ethical dilemmas within consumer-based datasets regarding human subject research, participant privacy, and informed consent in conversation with the principles of the seminal Belmont Report.

2020 ◽  
Vol 10 (4) ◽  
pp. 62
Author(s):  
Carlos Miguel Ferreira ◽  
Sandro Serpa

Visual communication is critical in contemporary societies. Research in social sciences increasingly tends to mobilize the image, for example, in the form of photography, in its processes (in the collection and interpretation of information) and products (in the communication of research results), which leads to the need to reflect critically on its specificities. This paper aims to add to the analysis of the potentialities, limitations and challenges of the use of photography in social sciences research. For this purpose, the paper presents and discusses empirically collected documentary expressions, selected from an organizational case study based on their heuristic capacity to illustrate the argumentation put forth herein. It is concluded that the potential of the use of photography in research in social sciences is high, but it is essential that the researcher considers, besides more technical aspects and ethical complexities, that photography is, in part, also the materialization of a certain socially constructed representation of reality.


Author(s):  
Gary Goertz ◽  
James Mahoney

Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. The book identifies and discusses major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, the book also seeks to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. The book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.


2021 ◽  
Vol 7 ◽  
pp. 237802312110244
Author(s):  
Katrin Auspurg ◽  
Josef Brüderl

In 2018, Silberzahn, Uhlmann, Nosek, and colleagues published an article in which 29 teams analyzed the same research question with the same data: Are soccer referees more likely to give red cards to players with dark skin tone than light skin tone? The results obtained by the teams differed extensively. Many concluded from this widely noted exercise that the social sciences are not rigorous enough to provide definitive answers. In this article, we investigate why results diverged so much. We argue that the main reason was an unclear research question: Teams differed in their interpretation of the research question and therefore used diverse research designs and model specifications. We show by reanalyzing the data that with a clear research question, a precise definition of the parameter of interest, and theory-guided causal reasoning, results vary only within a narrow range. The broad conclusion of our reanalysis is that social science research needs to be more precise in its “estimands” to become credible.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kjell Asplund ◽  
Kerstin Hulter Åsberg

Abstract Background Previous studies have indicated that failure to report ethical approval is common in health science articles. In social sciences, the occurrence is unknown. The Swedish Ethics Review Act requests that sensitive personal data, in accordance with the EU General Data Protection Regulation (GDPR), should undergo independent ethical review, irrespective of academic discipline. We have explored the adherence to this regulation. Methods Using the Web of Science databases, we reviewed 600 consecutive articles from three domains (health sciences with and without somatic focus and social sciences) based on identifiable personal data published in 2020. Results Information on ethical review was lacking in 12 of 200 health science articles with somatic focus (6%), 21 of 200 health science articles with non-somatic focus (11%), and in 54 of 200 social science articles (27%; p < 0.001 vs. both groups of health science articles). Failure to report on ethical approval was more common in (a) observational than in interventional studies (p < 0.01), (b) articles with only 1–2 authors (p < 0.001) and (c) health science articles from universities without a medical school (p < 0.001). There was no significant association between journal impact factor and failure to report ethical approval. Conclusions We conclude that reporting of research ethics approval is reasonably good, but not strict, in health science articles. Failure to report ethical approval is about three times more frequent in social sciences compared to health sciences. Improved adherence seems needed particularly in observational studies, in articles with few authors and in social science research.


2016 ◽  
Vol 59 ◽  
pp. 1-12 ◽  
Author(s):  
Roxanne Connelly ◽  
Christopher J. Playford ◽  
Vernon Gayle ◽  
Chris Dibben

2017 ◽  
Vol 22 (5) ◽  
pp. 469-476 ◽  
Author(s):  
Frank L. Schmidt

Purpose Meta-regression is widely used and misused today in meta-analyses in psychology, organizational behavior, marketing, management, and other social sciences, as an approach to the identification and calibration of moderators, with most users being unaware of serious problems in its use. The purpose of this paper is to describe nine serious methodological problems that plague applications of meta-regression. Design/methodology/approach This paper is methodological in nature and is based on well-established principles of measurement and statistics. These principles are used to illuminate the potential pitfalls in typical applications of meta-regression. Findings The analysis in this paper demonstrates that many of the nine statistical and measurement pitfalls in the use of meta-regression are nearly universal in applications in the literature, leading to the conclusion that few meta-regressions in the literature today are trustworthy. A second conclusion is that in almost all cases, hierarchical subgrouping of studies is superior to meta-regression as a method of identifying and calibrating moderators. Finally, a third conclusion is that, contrary to popular belief among researchers, the process of accurately identifying and calibrating moderators, even with the best available methods, is complex, difficult, and data demanding. Practical implications This paper provides useful guidance to meta-analytic researchers that will improve the practice of moderator identification and calibration in social science research literatures. Social implications Today, many important decisions are made on the basis of the results of meta-analyses. These include decisions in medicine, pharmacology, applied psychology, management, marketing, social policy, and other social sciences. The guidance provided in this paper will improve the quality of such decisions by improving the accuracy and trustworthiness of meta-analytic results. Originality/value This paper is original and valuable in that there is no similar listing and discussion of the pitfalls in the use of meta-regression in the literature, and there is currently a widespread lack of knowledge of these problems among meta-analytic researchers in all disciplines.


Sign in / Sign up

Export Citation Format

Share Document