The systematicity in science refers to the fact that scientific knowledge is not dispersed, but unified. These are part of a set, and only make sense in the relationship established with the elements of that set..
Science, for its part, is a systematic and logical process to discover how things work in the universe. To discover new knowledge, scientists and researchers go through a series of steps; question, research, hypothesis, experiment, data analysis and conclusions.
Science is also the body of knowledge accumulated through discoveries about all things in the universe. In this sense, the explanations offered by science are structured in a systematic way. These reflect the order and harmony present in reality.
Systematics in science allows scientific knowledge to be distinguished from other types of knowledge. This does not mean that other forms of knowledge are entirely unsystematic but, in comparison, they do exhibit a greater degree of systematicity..
This applies to knowledge on the same topic, not to any arbitrarily chosen area of knowledge..
Now, certain dimensions can explain this systematicity in science.
In formal sciences, such as logic or mathematics, a high degree of systematicity is achieved through the basic descriptions of their objects of study.
These objects are characterized by a complete and logically independent system of axioms..
On the other hand, empirical sciences use classification (taxonomies) or periodization (separation by phases or stages) as a resource for description.
In general, historical disciplines use narrative to explain why certain events or processes occurred, although the stories may contain theoretical or law-related elements.
They do this in a systematic way, being careful, for example, not to exclude possible alternative explanations..
In the empirical sciences, descriptions already have some explanatory power. In addition, theories are presented that greatly increase the systematicity of science due to its potential to provide unified explanations..
Several prediction procedures can be distinguished, although not all disciplines predict. The simplest case concerns predictions based on the regularities of empirical data.
When used in science, the prediction is usually much more elaborate than in everyday cases.
Science takes very seriously that human knowledge is constantly threatened by error.
This can have several causes: false assumptions, ingrained traditions, superstition, illusions, prejudices, biases and others. Science has its mechanisms for the detection and elimination of these sources of error.
In different areas of science, there are ways to defend your claims. In the formal sciences, for example, they eliminate error by providing a proof for any statement that is not an axiom or a definition..
On the other hand, in the empirical sciences, empirical data play a preeminent role in defending claims to knowledge..
Scientific knowledge has more articulated connections with other pieces of knowledge than, above all, everyday knowledge..
In addition, there are transitional areas between scientific research and related activities that are more directed towards practical ends.
Science makes constant efforts to improve and expand the body of knowledge. Modern natural science especially, has seen remarkable growth, both in scope and precision..
Science is systematic in having a goal of complete knowledge and systematic in achieving this goal.
It is constantly on the move to systematically improve existing data and obtain new ones, it exploits other bodies of knowledge for its own purposes, and it systematically forces chance to improve its knowledge..
Scientific knowledge is not just a messy aggregate, it is structured thanks to its intrinsic epistemic connection.
An adequate representation of knowledge must take into account this internal structure.
In short, systematicity can have several dimensions. What characterizes science is the greatest care in excluding possible alternative explanations, the most detailed elaboration with respect to the data on which the predictions are based, the greatest care in detecting and eliminating sources of error, among others..
Thus, the methods used are not unique to science, but it is necessary to be much more solicitous with the way of applying the methods..
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