It has become abundantly clear to me social science research is meant to be conducted ethically, following the scientific method and be both qualitative and quantitative. Good ethics translates to good science, and when cases where the ethics follow a questionable track, the results cast doubt on the quality of the result. As McArthur is critical of the Milgram experiments, he states “The research subjects were subjected to psychological harm without appreciating the risks from the beginning, deception was used without what today would count as acceptable debriefing and so on.” (McArthur, 2008, p. 70), thus indicating clear, fundamental flaws in the Milgram experiments and how they are an excellent and instructive example of bad ethics precipitating conclusions. In addition, by following the scientific method and leveraging peer review, researchers are able to avoid other issues with research integrity, such as the issues with Diedrik Stapel and his bogus research claims with manufactured data. Finally, by leveraging both qualitative and quantitative methodologies for gathering data, we are better able to overcome the challenges of being mono-method researchers, and better contribute to the realm of social sciences.
Conducting social science research involves the collection of data, from both primary and secondary sources, which can be gathered ethnographically, from archives, surveys, interviews and observations. By identifying a topic of interest, determining the research questions to be answered, and developing a hypothesis, one then determines which of the data collection methods best align with the research questions, and goes about creating a research plan. The plan involves determining demographics such as target group, geographical locations, ethical considerations, participant or non-participant observation, and how to disseminate the data. When gathering data from archival institutions, important considerations should be made relating to data archival guardians, as Tesar notes “guardians themselves and their actions are governed by complex legislation that they are left to interpret in order to protect the institution” (Tesar, 104), thus ensuring ethical considerations by ensuring privacy and confidentiality, and eliminating bias. When disseminating statistical research data, one must determine if variables within datasets have relationships, their nature and pattern, and how they inform the narrative. One can then identify correlations and, through them, describe cause and effect within their research framework. Finally, when conducting research, it is important to consider “ghostly” social and cultural aspects to ensure the researcher “captures perfectly the paradox of tracking through time and across all those forces that which makes its mark by being there and not there at the same time” (Gordon, Radway, 6), or put simply, ensures capturing the complexity of human experiences.
When designing a research project, I learned the importance of formulating a research question, and how a well-defined research question lays the foundation for conducting and gathering research. I also learned the importance of choosing the appropriate methodology for gathering, analyzing and presenting data. Whether my approach relies on empirical evidence via a positivist approach, or learning through social interaction via a constructivist approach (Armstrong, 29), I learned how each framework helps relate to different aspects of social reality and how the blending of the two can highlight different power dynamics, customs and even uncover biases within the data. I learned how the information gleaned from quantitative visualization of data can reveal trends and gaps, which can also influence how I answer my research question. With the visualization of quantitative data, owing its roots to thematic cartography, making “the properties of empirical numbers- their trends, tendencies, and distributions- more easily communicated, or accessible to visual inspection” (www.datavis.ca), it serves as a valuable tool for complementing qualitative research methodologies, such as interviews and the analyzing of content.
I learned the value of using different data analysis tools, such as Excel, Tableau and ATLAS.ti, and how the use of these tools for the visualization of data can enable the social science researcher to better understand our social world. It is through the use of these tools one understands the importance of data integrity and how, as a researcher, your reputation and the integrity of your work is a reflection of the integrity and visualization of the data.
With a well formed research question in hand, conducting social science research is a complex data collection process from primary and secondary sources, requiring careful planning and ethical considerations. With integrating these considerations with statistics gathering and dissemination, and drawing meaningful relationships between variables and datasets, along with capturing the complexity of human experience, one can perceive and interpret social phenomena through the dissemination of data. Leveraging qualitative and quantitative data, by using a multitude of tools and frameworks for analyzing and visualizing data, opportunities arise to see relationships and additional insights into the subject matter being studied, that wouldn’t normally appear if one focused solely on one methodology over the other. With all of these elements in hand, they combine to ensure research is not only up to moral standards, but the research data is credible, the methods for collecting it are varied, thus ensuring the highest quality outcomes. Armed with these elements, frameworks and standards, I now see myself, not only as a social science researcher, but a critical thinker who can better understand and inform my family, community and society.
Works Cited
McArthur, D. (2008). Good ethics can sometimes mean better science: research ethics and the Milgram Experiments. Science and Engineering Ethics, 15(1), 69–79. https://doi.org/10.1007/s11948-008-9083-4
Tesar, M. (2015). Ethics and truth in archival research. History of Education: Journal of the History of Education Society, 44(1), 101-114. https://doi.org/10.1080/0046760X.2014.918185
Gordon, A. F., & Radway, J. A. (2008). Ghostly matters: Haunting and the sociological imagination (pp. 3-28). University of Minnesota Press.
Armstrong, J. (2013). Positivism and Constructivism. In: Improving International Capacity Development. Palgrave Macmillan, London. https://doi.org/10.1057/9781137310118_3
Milestones in the history of thematic cartography, statistical graphics, and data visualization. (n.d.). https://www.datavis.ca/milestones/index.php?page=introduction