What is empirical research in the social sciences?

Experimental or empirical research in the social sciences aims to decipher how the world works around us, especially in some disciplines where researchers try to explain how some parts of the world are built and operate, for example, development studies, economics, sociology, political science, or geography. For example, political scientists try to explain why some people vote while others abstain from voting. Researchers in development studies may consider the effect of foreign aid on economic growth in the recipient country. Education researchers might study how the number of students in a class affects the learning outcomes of high school students, and economists might be interested in the effect of raising the minimum wage on job growth. Social science researchers attempt to explain the behavior of individuals such as voters, protesters, and students. or the conduct of groups such as political parties, corporations, or social movement organizations; or the behavior of macro-level units such as countries and states.

While the tools and methods we will refer to are applicable to all disciplines of the social sciences, the article will give examples of empirical political science, in all social sciences and political science, in particular, knowledge acquisition can be normative and empirical. Normative political science raises the question of how the world should be. For example, normative democracy theorists grapple with the question of what a democracy should be. Is it a process in which free, fair and normal elections are allowed, which is referred to in democratic literature as the “minimum definition of democracy”. Or should a country, in addition to a fair electoral process, grant a variety of political rights (such as freedom of religion, freedom of assembly), social rights (such as the right to health care and housing), and economic rights (such as the right to education or housing) To become a “really” democrat? This more comprehensive definition is currently referred to in the literature as the “maximum definition of democracy”.

While normative and empirical research have fundamentally different goals, they are nonetheless complementary. To shed light on this, researchers of empirical democracy have to define a specific criterion by which a country is defined and symbolized as a democratic or non-democratic state. This criterion can only be determined through normative means. Normative political science (theory) should establish the so-called “gold standard” by which empirical political scientists can test whether a country is a democracy.

Thus, empirical political science is less concerned with what a democracy should be like than with how a democracy behaves in the real world. For example, an empirical researcher can ask the following questions: Do democracies have more women’s representation in parliament than non-democratic countries? Is military spending less in democracies than in authoritarian or hybrid regimes? Or is history in secondary schools different in democracies than in other systems? Do democracies spend more on social services than do authoritarian regimes? Answering these questions requires observation and empirical data. Whether collected at the individual level through interviews or surveys, at the intermediate level, e.g., through membership data of associations or social movements, or at the aggregate level through government/international agencies or statistical offices, in all cases the data collected should be of high quality.

Ideally, the researcher should clearly define the measurement and data collection processes for any study so that others can repeat the same study. Ultimately, our goal is to gain interchangeable or generalizable knowledge. Interaction means that if two people engage in the same data-collection process and conduct the same pilot study, their findings should be the same. In order for empirical political science to be as realistic or “fact-based” as possible, it must adhere to the following criteria:

  1. Falseability: The falsifiability model implies that data or hypotheses can be proven or refuted. For example, we can test in practice the hypothesis that “democracies do not go to war with each other.” After determining what war and what democracy is, we can get data that fits our definition of the type of regime in a country from a reliable source such as the Center for Comprehensive Peace (CSP), and conflict/war data can be obtained from another high-quality source such as the Oslo Peace Research Institute (PRIO). In the second stage, we can then use statistics to test whether democracies refrain from engaging in war with one another is true.
  2. Repeatability: The process is also called the ability to transfer and repeat the results or project them to other cases, and iteration refers to the process through which previous results can be retested as well. Retesting could involve either the same data or new data from the same pilot surveys. For example, it is possible to retest data on the “almost taken for granted hypothesis” that democracies do not go to war with each other every five years with the help of the most recent data from the credible sources cited earlier, which gives us an idea of ​​whether this The hypothesis is still valid or not. Repetition involves high scientific standards; It will not be possible to repeat a study unless the data collection tools, data source, and methods of data analysis are clarified and explained in any research. Then the “replicating” researcher should use these same data and methods to study similar cases.
  3. Cumulative Nature: Empirical scientific knowledge is cumulative. This means that objective results and research methods are based on prior knowledge. In short, researchers don’t start from scratch or intuition when participating in a research project. Rather, they try to confirm, modify, expand or build on previous research and knowledge. For example, the statement that democracies avoid war among themselves has been confirmed and reconfirmed many times in recent decades. Having asserted that democratic peace theory in its initial form is well-established, researchers have attempted to extend the democratic peace model and examined, for example, whether countries that share the same economic system (such as neoliberalism) are not also at war with each other. However, for the latter relationship, tests and reviews have shown that the empirical link to peace economic system is less robust than democratic peace theory. The same goes for another possible expansion, which is to look at whether democracies are generally less inclined to go to war than non-democracies. Here, too, the empirical evidence is negative or inconclusive at best.
  4. Generalization: In empirical sociology, we are interested in general explanations rather than specific ones; We are interested in the limitations of empirical data. Does the empirical data apply to only one case (eg, does it explain only why the US and Canada never go to war), or can it be generalized to explain many cases (eg, does it explain why not all democracies go to war?) In other words, If it can be generalized, does the democratic peace model apply to all democracies, or only to neoliberal democracies, and does it apply to all (normative) definitions of democracies, as well as to all time periods? In other words, we are interested in the number of cases in which these findings apply. Of course, the wider the applicability of the interpretation, the greater its weight. In political science, the theory of democratic peace is among the theories that can be applied on the widest scale. Although there are some dubious cases of conflict between countries such as the conflict between Turkey and Greece over Cyprus in 1974, no case has emerged so far that clearly refutes the theory of democratic peace. Indeed, democratic peace theory is one of the few law-like rules in political science.

In the end, experimentation can be applied in the social sciences, in a different way from that in the natural sciences. The matter starts from linking the standard and empirical definitions of phenomena and cases, then passes to obtaining individual, group or total data of high quality, then comparison and drawing conclusions, which must It is characterized by a number of characteristics, including the ability to falsify, repetition, cumulative, and generalizability.

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