In this blog post, we will examine the characteristics of scientific progress based on Thomas Kuhn’s ‘The Structure of Scientific Revolutions’ and explore whether his theory can be applied to all scientific fields.
Thomas Kuhn’s view on the development of science is that it does not progress in a continuous, cumulative manner, but rather through discontinuous revolutions. Today, the phrase “paradigm shift” is commonly used in advertisements and speeches to emphasize a new change that is entirely different from the past. The term “paradigm” here refers to a way of thinking or a framework of understanding. This term gained widespread recognition through Thomas Kuhn’s book ‘The Structure of Scientific Revolutions’. Kuhn used this concept to explain how science develops. The fact that this term has since been applied beyond science to various fields—such as society, economics, and culture—is likely because the patterns of change in these fields bear some resemblance to the process of scientific development. However, the question remains as to whether every field within science itself can be explained by the concept of a paradigm as proposed by Kuhn. In this article, I will examine Kuhn’s theory of scientific development, focusing on ‘The Structure of Scientific Revolutions’, and reflect on its scope of application.
The core of Thomas Kuhn’s theory of scientific development is that science does not change in an accumulative or continuous manner, but rather develops in discrete stages. He explains that when a particular normal science faces a crisis, a scientific revolution occurs, and a new normal science based on a new paradigm emerges. According to Kuhn, normal science refers to research activities built upon one or more past scientific achievements; it signifies the body of work recognized by a specific scientific community as the foundation for research over a certain period. If an “anomaly”—a phenomenon difficult to explain using existing theories—arises during the course of such normal science, the existing normal science faces a crisis. To resolve this crisis, a new scientific theory emerges; as a result, a scientific revolution occurs, a new normal science is formed, and science progresses.
As representative examples of how scientific progress occurs in discrete stages, Kuhn cited Copernicus’s astronomy, Lavoisier’s theory of oxygen, and Einstein’s theory of relativity. Taking the Copernican Revolution as an example, the existing “normal science” was Ptolemy’s geocentric model. This theory had long been quite successful in predicting the positions of the planets. However, over time, difficulties arose in explaining various astronomical phenomena, and various modifications were made within the existing framework to resolve these issues. Yet these adjustments gave rise to new problems, and eventually, the existing theory faced a crisis. Subsequently, Copernicus’s heliocentric theory emerged as a new paradigm, replacing the existing normal science, and this became an example of a scientific revolution.
The most important concept in Kuhn’s theory of scientific development is “discrete progress.” He argued that the process of moving from a pre-paradigm era to the acceptance of a new theory is mostly accompanied by the collapse of the existing paradigm and conflict among competing schools of thought, and that the simple accumulation of unexpected new discoveries is a very rare exception in the development of science.
However, it is questionable whether this explanation can be directly applied to fields with a strongly cumulative nature, such as biology or geology. The examples Kuhn primarily cited were fields like physics and chemistry, where revolutionary shifts were relatively distinct. Of course, modern biology has also experienced significant conceptual shifts, such as the emergence of molecular biology or the discovery of the structure of DNA, but many subfields have developed by continuously building upon existing research. Geology, too, has seen major paradigm shifts such as plate tectonics, but a significant portion of research takes the form of gradually expanding existing knowledge. Therefore, there remains room for discussion as to whether all scientific fields can be explained in the same way.
Take anatomy, for example. Anatomy is the discipline that studies the structure, form, location, and interrelationships of the cells, tissues, organs, and organ systems that make up living organisms, and it is a fundamental discipline of great importance in medical education. While the structure of living organisms changes over the long timescale of evolution, it does not change rapidly in the short term. Consequently, the methodologies used to study it are also more likely to undergo a process of continuous accumulation and refinement rather than sudden changes. Of course, while research methods have advanced with the introduction of new imaging technologies and molecular biological research techniques, the basic framework for understanding the subject matter itself has remained relatively stable. Given these characteristics, it may be more natural to describe anatomy as a field that has long developed within a single normal science.
Conversely, if we base our analysis solely on the concepts of paradigms and normal science, we can view social phenomena such as political systems as having a similar structure. Throughout human history, political systems have tended to change gradually within a single framework before transitioning to a new system through major events such as revolutions or democratization. In the case of South Korea, the June Democratic Uprising of 1987 marked a crucial turning point in the transition from an authoritarian regime to a democratic one. Interpreted through Kuhn’s concepts, this can be viewed as a case where the paradigm of authoritarianism faced a crisis and shifted to a new paradigm of democracy. However, generally speaking, few people consider political systems to be more scientific than biology or geology.
Of course, just because “If A, then B” holds true does not mean that “If B, then A” also holds true. The fact that political systems share characteristics similar to the structure of scientific revolutions as described by Kuhn does not automatically mean they are science. However, it is somewhat puzzling that while Kuhn’s theory fails to adequately explain certain fields generally recognized as science, it instead applies similarly to areas that are not science. So, does Kuhn’s theory truly explain the “structure of scientific revolutions”? Or is it a theory that explains the “structure of revolutions” in a broader sense? Or is it perhaps a theory better suited to explaining the patterns of development in specific fields, such as physics or chemistry?
In this regard, I believe Kuhn’s theory needs to present clearer criteria for distinguishing between science and non-science. A prime example of such a criterion is Karl Popper’s theory of falsifiability. Popper argued that a scientific theory must be open to criticism and verification and must be capable of being falsified. Here, “falsifiability” does not mean acknowledging the possibility that a theory might be wrong, but rather that there exists a method to actually test the theory and confirm that it is incorrect. For example, while the proposition “All swans are white” cannot be proven true by examining every swan, it can be proven false if even a single black swan is discovered.
It does not necessarily have to be Popper’s theory. However, if we present these criteria for defining science alongside it, we can clearly explain fields such as biology and geology as sciences, while at the same time supplementing Kuhn’s concept of “normal science” in a more persuasive manner.
Another approach is to define the subject of analysis more specifically. For example, rather than relying on a single general theory like ‘The Structure of Scientific Revolutions’, it might be more appropriate to analyze the developmental processes of individual academic fields—such as physics, chemistry, and biology—separately. Since the subjects of study and methodologies vary significantly across scientific disciplines, discussing development models that reflect the unique characteristics of each field would allow for a deeper understanding of scientific progress.
