Learning Objectives
By the end of this section, you will be able to:
- Understand the difference between qualitative and quantitative methods
- Recount the discourse surrounding the two methodological currents
- Review mixed-methods research
Along with the two major waves of institutionalism and behavioralism, there are two major currents in political science: the qualitative methodological current and the quantitative methodological current. Just like their ocean counterparts, these methodological currents help determine how political scientists attempt to understand the world. And just like ocean currents help to regulate and stabilize global climate patterns, quantitative and qualitative methods help regulate and stabilize the scientific inquiry. Methods are simply the steps taken by social scientists during their research. They are the techniques used to collect, construct, and consider data. By using replicable methods, or research steps that can be duplicated by other scholars, this allows political scientists to use the scientific method in their inquiries (this is discussed more in Chapter Three: The Scientific Method)
Qualitative methods are defined by Flick (2018) as “research interested in analyzing the subjective meaning or the social production of issues, events, or practices by collecting nonstandardized data and analyzing texts and images rather than numbers and statistics”. What this means is that researchers try to solve puzzles in political science without using some type of mathematical analysis or using a simple mathematical measurement, such as coding of text and/or images. Quantitative methods are defined by Flick (2018) as “research interested in frequencies and distributions of issues, events, or practices by collecting standardized data and using numbers and statistics for analyzing them”. What this means is that political scientists solve puzzles using mathematical analysis or mathematical measurement.
Shively (2017) more elegantly states that quantitative research is attentive to, “numerical measures of things...to make mathematical statements about them. Whereas qualitative research is “less concerned with measuring things numerically and tends to make verbal statements about them.” Baglione (2018) more simply states that it comes down to the use of numbers versus the use of words as the evidence used to draw conclusions. The obvious differences between the two currents has led to a potential divide in the field of political science - those who use qualitative methods, specialize in them, and prefer these approaches, such as ethnological research, case study (or small-n), or archival work (Chapter Seven); and those who use quantitative methods and develop and implement mathematical and statistical techniques, such as analyzes of datasets and formal modeling (Chapter Eight).
As expected, the behavioral revolution created a wedge among political scientists. Qualitative research scholars often scoffed at the opaqueness of mathematical techniques made ever more complex by quantitative methodologists. They also bemoaned the lack of applicability of some of these developments, often calling the papers, “math for math’s sake”. In response quantitative scholars viewed traditional qualitative techniques, such as archival work as antiquated, or newer techniques, such as interpretivism, as non-inferential, and thus of less use.
The clash of currents between qualitative and quantitative methodology reached its peak in the 1990s, when the book Designing Social Inquiry: Scientific Inference in Qualitative Research (DSI) came out in 1994. Written by Gary King, Robert O. Keohane, and Sidney Verba (1994), DSI suggests that qualitative research would improve if they adopted some of the tools used by quantitative scholars. These tools include better defining the research problem, identifying which theories to draw hypotheses from, case selection, testing and retesting to further clarify the theory. As expected quite a few qualitative scholars did not appreciate what they viewed as a talking down to by notable scholars in the discipline. Though this was not the intent of DSI, as its goal was to shrink the divide between the two currents. Nevertheless, this was not how it was received.
The major countercurrent to DSI was the book edited by Henry E. Brady and David Collier (2004), Rethinking Social Inquiry: Diverse Tools, Shared Standards (RSI). In RSI, Brady and Collier appreciate the effort by King, Keohane, and Verba (1994) to bridge the divide between the two methodological currents. However, they are concerned that DSI overemphasizes the importance of quantitative tools when designing qualitative research agendas. Charles Ragin (2004), one of the contributors to the volume, contends that the key goal of qualitative research - inference, is not much different from the goal of qualitative research - making sense of cases.
Both sets of scholars have the same objective, albeit with different means of getting there. Additionally, contributing authors, such as Gerardo Munck (2004), detailed qualitative tools for each step of the research process, focusing on case selection, measurement and data collections and assessing causation.
A more critical countercurrent to DSI was the Perestroika movement in political science, where qualitative scholars critiqued the dominance of quantitative methodology in the discipline, including the elected leadership of the American Political Science Association (APSA). Calling themselves an intellectual rebellion, the authors in their book Perestroika, push for a pluralistic future of political science, where all methods are respected and treated fairly. Shapiro (2005) comments that political science has become too method-driven, and instead should be more problem-driven. And that if method selection drives the analysis, then it leads to what he calls the “self-serving construction of problems”. Finally, the study of normative politics, and the importance of narratives and discourse to contextualize the study of politics has substantive value. Sacrificing substance at the altar of mathematics and statistics, Sanders (2005) argues is shortsighted.
Has the clash of currents subsided? Not really. Qualitative scholars contend that the flagship journal American Political Science Review (APSR) is still “hostile to qualitative concerns in the discipline” (McGovern 2010). However, a newer current within the discipline has developed to respond to the concerns of these scholars: the Qualitative and Multi-Method Research section of APSA. The goals of this research section are to further discussion within quantitative methodology and investigate how the various branches of methodology interact. Also referring to the latter goal as mixed-methods research, Creswell and Clark (2017) describe it as research involving both quantitative and qualitative data.
Quantitative data consists of closed-ended information. This can include interval or ratio scale data (more on this in Chapter Eight), often asked in surveys. Whereas qualitative data includes open-ended information that is often gathered through interviews or observation. Mixed-methods research is simply the mixture of close-ended and open-ended techniques to triangulate the right conclusions. Are mixed methods the future methodological current of political science? It is premature to suggest that this is the case. Graduate students are still likely to specialize in a methodological current. However, what is sure is that the current of quantitative methodological supremacy has receded enough to allow other currents to reach the shore.
