Cognition - this is a specific type of activity, aimed at comprehending the world around and oneself in this world.

Analysis (Greek decomposition) - the division of an object into its component parts for the purpose of their independent study. Analysis task: from various kinds of data to compile a general holistic picture of the process, to identify its inherent patterns, trends. From the standpoint of dialectics, analysis is seen as a special technique for studying phenomena and developing theoretical knowledge about these phenomena. The main cognitive task of dialectical analysis is to single out its essence from the variety of aspects of the subject under study, not by mechanically dividing the whole into parts, but by isolating and studying the sides of the main contradiction in the subject, to discover the basis that connects all its sides into a single integrity, and to bring to this basis is the regularity of the developing whole. Types of analysis: mechanical dismemberment; definition of dynamic composition; identification of forms in/action of the elements of the whole.

Synthesis (Greek connection) - a real or mental union of various sides, parts of an object into a single whole. Synthesis is considered as a process of practical or mental reunification of the whole from parts or the connection of various elements, sides of the subject into a single whole, a necessary stage of knowledge. Modern science is characterized not only by intra-, but also by interdisciplinary synthesis. The result of synthesis is a completely new formation, the properties of which are not only an external connection of the properties of the components, but also the result of their internal interconnection and interdependence.

Induction ) is a logical research method associated with the generalization of the results of observations and experiments and the movement of thought from the singular to the general. Inductive conclusions always have a probabilistic character. Types of inductive generalizations: a) popular induction, when regularly repeating properties observed in some representatives of the studied set (class) and fixed in the premises of inductive reasoning are transferred to all representatives of the studied set (class) - including its unexplored parts. (for example, the fact of the presence of black swans). b) Induction incomplete– all representatives of the studied set own the property “n” on the grounds that “n” belongs to some representatives of this set. For example, some metals have the property of electrical conductivity, which means that all metals are electrically conductive. in) full induction, in which the conclusion is made that all representatives of the studied set have the property “n” on the basis of the information obtained during the experimental study that each representative of the studied set has the property “n”. G) Scientific induction, in which, in addition to the formal substantiation of the generalization obtained by induction, a substantive additional substantiation of its truth is given, including with the help of deduction.

Deduction - firstly, the transition in the process of cognition from the general to the particular, the derivation of the individual from the general; secondly, the process of logical inference, that is, the transition, according to certain rules of logic, from certain given sentences - premises to their conclusions. Deduction prevents the imagination from falling into error, only it allows, after the establishment of new starting points by induction, to deduce consequences and compare conclusions with facts. Deduction can provide testing of hypotheses.

Analogy - the method of scientific knowledge in which the similarity is established in certain aspects, as well as in relations between non-identical objects. Inference by analogy - the conclusions that are made on the basis of such a similarity. So, when deriving by analogy, the knowledge obtained from the consideration of an object is transferred to another, less studied and less accessible object for research. Analogy does not give reliable knowledge. To increase the likelihood of inferences by analogy, it is necessary to strive to ensure that: a) the internal rather than external properties of the objects being compared are captured; b) these objects were similar in the most important and essential features, and not in random and secondary ones; c) the circle of matching signs was as wide as possible; d) not only similarities were taken into account, but also differences - so that the latter would not be transferred to another object.

Modeling as a method of scientific knowledge is the reproduction of the characteristics of some object on another object, specially created for their study

. Model - an object that is similar in some respects to the prototype and serves as a means of describing and / or explaining and / or predicting the behavior of the prototype. The need for modeling arises when the study of the object itself is impossible, difficult, expensive. There must be a certain similarity between the model and the original, which allows you to transfer the information obtained as a result of the study of the model to the original. At physical (subject) modeling of a specific object, its study is replaced by the study of some model that has the same physical nature as the original (aircraft models). With ideal (sign) modeling models appear in the form of diagrams, graphs, drawings. Ideal modeling is “mental modeling”: 1) Visual modeling is performed on the basis of the researcher's ideas about a real object by creating a visual model that displays the phenomena and processes occurring in the object. Visual modeling: 1.1. At hypothetical simulation a hypothesis is laid about the patterns of processes in a real object, which reflects the level of knowledge of the researcher about the object and is based on cause-and-effect relationships between the input and output of the object under study. 1.2 Analog simulation based on the use of analogies of various levels. 1.3. Mock Modeling associated with the creation of a mock-up of a real object at a certain scale and its study. 2) Symbolic modeling- this is an artificial process of creating a logical object, which replaces the real one and expresses its main properties using a certain system of signs and symbols. Symbolic modeling is usually divided into linguistic and symbolic. 3) Mathematical modeling based on the description of a real object with the help of a mathematical apparatus.

Classification- division of a set (class) of objects into subsets (subclasses) according to certain criteria. In the scientific classification, the properties of an object are put in a functional relationship with its position in a particular system. There are artificial and natural classifications: in contrast to the artificial (it is based on insignificant similarities and differences of the object, for the systematization of objects (alphabetic catalog), in the natural classification according to the maximum number of essential features of the object, its position in the system is determined (for example, natural system of organisms, Mendeleev's periodic system of elements).

Analysis. Under analysis understand the division of an object (mentally or actually) into its component parts for the purpose of their separate study. Such parts may be some material elements of the object or its properties, features, relationships, etc. Analysis is a necessary stage in the cognition of the object.

During synthesis the component parts (sides, properties, features, etc.) of the object under study, dissected as a result of the analysis, are joined together. On this basis, further study of the object takes place, but already as a single whole. At the same time, synthesis does not mean a simple mechanical connection of disconnected elements into a single system. It reveals the place and role of each element in the system of the whole, establishes their interrelation and interdependence, i.e., allows us to understand the true dialectical unity of the object under study.

Analysis and synthesis are also successfully used in the sphere of human mental activity, that is, in theoretical knowledge. But here, as well as at the empirical level of knowledge, analysis and synthesis are not two operations separated from each other.

Analogy- a method of cognition that allows, based on the similarity of objects in one way, to draw a conclusion about their similarity in others. Analogy is called inference from the singular to the singular or from the particular to the particular.

Close to analogy is the method comparisons , allowing to establish not only the similarity, but also the difference between objects and phenomena. Analogy and comparison do not have great explanatory resources, but they help to establish additional connections and relations of the object. Analogy and comparison allow us to put forward new hypotheses and thus contribute to the development of scientific knowledge.

Modeling- this is the operation of an object that is an analogue of another, for some reason inaccessible to manipulation. Thanks to modeling, it is possible to penetrate into the inaccessible properties of an object using its analogue. Based on the knowledge obtained with the help of the model, a conclusion is made about the properties of the original. The basis of modeling is the reception of analogy.

Ethical principles of scientific research:

The intrinsic value of truth

Initial criticism

Freedom of scientific creativity

The novelty of scientific knowledge

Equality of scientists in the face of truth

The Public Availability of Truth

Bioethics is a direction on the border of science and the system of human values. He studies a complex of problems associated with any interference in the life of living systems (transplantation, genetic engineering, resuscitation, new reproductive technologies, the status of the human embryo, the problem of human death, including euthanasia)

Pseudo-scientific activity(alchemy, astrology, etc.) preceded science and later went along with science. Modern pseudoscience, like real science, is very heterogeneous in composition. This includes various esoteric, mystical teachings, the practical activities of sorcerers, magicians, psychics. These teachings, which can be called parascientific (from the Greek. para- "about"), in fact, do not need scientific justification. The scientific status they aspire to is needed

only to increase their rating, authority. Such pseudosciences include parapsychology, bioenergetics, the doctrine of the biofield, astrology, etc. Pseudoscientific ideas also arise in the depths of real science, when scientists “forget” about scientific methods, scientific ethics, trying to make a scientific revolution from scratch. The objects of study of such pseudoscientists are unidentified flying objects (ufology), torsion and information fields, laser-holographic properties of biological objects and other problems of the so-called deviant science.

For the CDS, the stages of formation - the history of the development of the KSE

Scientific methods of theoretical research.

1. Theoretical analysis and synthesis. elemental analysis. Analysis by units.

2. Methods of abstraction and concretization. Rising from the abstract to the concrete.

3. Modeling method.

4. Thought experiment as a kind of modeling.

5. Induction and deduction.

6. Formalization.

7. Hypothetical-deductive method, its essence.

8. Axiomatic method.

The theoretical level of scientific knowledge reflects the phenomena and processes from the side of their universal internal connections and regularities, this is achieved by rational processing of data of the empirical level of knowledge. Therefore, it involves all forms of thinking - concepts, judgments, inferences, general logical methods, as well as methods associated with mental operations - abstraction, idealization, formalization, etc.

The purpose of the theoretical level is not only to establish the facts and reveal external connections between them, but also to explain why they exist, what caused them, to identify the possibilities for their transformation.

Theoretical methods (and this is their shortcoming) do not have a direct impact on the variety of observed facts, however, they make it possible to discover hidden patterns in facts, general, necessary, essential, to understand the mutual influence of factors determining development.

The truths that are revealed by the methods of theoretical research are theoretical truths that are verified directly, not by empirical, practical means, but by proof. In substantiating theoretical truths, practice takes part indirectly, through truths that have already been verified before. This is due to the composition of this method.

The most important difference between theoretical knowledge and empirical knowledge is that it makes it possible to transfer conclusions obtained under certain conditions and on the basis of the analysis of certain objects to other conditions and objects, including those that do not yet exist, designed, created mentally, in the imagination. .

Let's move on to characterizing the methods of theoretical research (cognition).

Theoretical analysis and synthesis. elemental analysis. Analysis by units.

originality method of theoretical analysis and synthesis in its universal capabilities to consider the phenomena and processes of reality in their most complex combinations, to single out the most significant features and properties, connections and relationships, to establish the patterns of their development.

Analysis(Greek - decomposition, dismemberment) - the division of an object into its component parts for the purpose of their independent study.

Analysis task is to from various kinds of data reflecting individual phenomena and facts, to compile a general holistic picture of the process, to identify its inherent patterns, trends.

The characteristics of the analysis deserve special attention. from the standpoint of dialectics, where it is considered as a special technique for studying phenomena and developing theoretical knowledge about these phenomena. The main cognitive task of dialectical analysis is to isolate its essence from the variety of aspects of the subject being studied not by mechanically dividing the whole into parts, but by isolating and studying the sides of the main contradiction in the subject, to discover the basis that connects all its sides into a single integrity, and to derive on this basis the regularity of the developing whole.

In social work, analysis acts as a method or way of knowing social reality.

Analysis is applied both in real (practice) and in mental activity. There are several types of analysis:

Mechanical dismemberment;

Definition of dynamic composition;

Identification of forms of interaction of elements of the whole;

Finding the causes of phenomena;

Identification of levels of knowledge and its structure;

Analysis by elements (elementary) and analysis by units.

Elementary Analysis- this is a mental selection of individual parts, connections based on decomposition, dismemberment of the whole. Say, when studying real social processes, phenomena, contradictions, aggregates that contain contradictions and give rise to a problem situation, it is possible to isolate separately their goals, content, external conditions, technology, organization, system of relations of its subjects for analysis.

Unit Analysis involves the dismemberment of the process while maintaining the integrity of its elementary structural elements, each of which holds the most important features of a holistic process. In the activity of the client of a social work specialist, this can be an act, in socio-pedagogical design - the social situation of personality development.

After performing the analytical work, there is a need for synthesis, integration of the results of the analysis in a common system.

Synthesis (Greek - connection, combination, composition) - the union, real or mental, of various sides, parts of an object into a single whole.

In the dictionary of the Russian language S.I. Ozhegov synthesis interpreted as a method of studying a phenomenon in its unity and interconnection of parts, generalization, bringing together data obtained by analysis.

Thus, synthesis should be considered as the process of practical or mental reunification of the whole from parts or the combination of various elements, sides of an object into a single whole, a necessary stage of knowledge.

The result of synthesis is a completely new formation, the properties of which are not only an external connection of the properties of the components, but also the result of their internal interconnection and interdependence.

Analysis and synthesis are dialectically interconnected. They play an important role in the cognitive process and are carried out at all its stages.

The methods of abstraction and concretization are closely related to the methods of analysis and synthesis.

2. Abstraction (lat. - distraction)- mental abstraction of any property or attribute of an object from its other attributes, properties, connections ( concept for research in social work) .

This is done in order to study the subject more deeply, to isolate it from other subjects and from other properties, signs.

In order to penetrate into the essence of social phenomena, to reveal the invariant features of the process under study, it is necessary to isolate the subject of study in its “pure” form, to be able to dissociate itself from all side influences, to abstract from all the numerous connections and relationships that prevent us from seeing the most significant connections and characteristics that interest us as researchers.

For example, in order to identify the educational potential of society, it is possible at the 1st stage to abstract from the conditions of the socio-economic crisis, political struggle, the pedagogical failure of many families and consider in a “pure” form (without interference, inhibitory influences) the educational opportunities of the family, school, cultural institutions, law enforcement agencies, government and commercial structures, public organizations.

There are different types of abstractions:

– identification abstraction, as a result of which the general properties and relations of the studied methods are singled out (the rest of the properties are disregarded). Here the classes corresponding to them are formed on the basis of establishing the equality of objects in given properties or relations, the identical in objects is taken into account and abstraction from all differences between them takes place;

– isolating abstraction- acts of the so-called "pure distraction" in which certain properties and relations are distinguished, which begin to be considered as independent individual objects ("abstract objects" - "kindness", "empathy", etc.);

– abstraction of actual infinity in mathematics– when infinite sets are considered as finite. Here the researcher is distracted from the fundamental impossibility of fixing and describing each element of an infinite set, taking such a problem as solved;

– potential feasibility abstraction- is based on the fact that any, but a finite number of operations can be carried out in the process of mathematical activity.

Abstractions also differ in levels (orders). Abstractions from real objects are called first-order abstractions. Abstractions from abstractions of the first level are called abstractions of the second order, etc. The highest level of abstraction is characterized by philosophical categories.

The limiting case of abstraction is idealization . Idealization is the mental construction of concepts about objects that do not exist and are not feasible in reality, but those for which there are prototypes in the real world.

The basis of abstraction during idealization is taken from the connections and qualities of phenomena that exist in principle or are possible, but the abstraction is carried out so consistently, the subject is so completely isolated from the accompanying conditions that objects are created that do not exist in the real world.

That is, in the process of idealization, there is an extreme abstraction from all the real properties of the object and, at the same time, features that are not realized in reality are introduced into the content of the formed concepts. As a result, a so-called “idealized object” is formed, which can be used by theoretical thinking when reflecting real objects.

However, it is precisely these idealized objects that serve as models that make it possible to reveal much deeper and more fully some of the connections and patterns that are manifested in many real objects.

Instantiation method in its logical nature is the opposite of abstraction. It consists in a mental reconstruction, a re-creation of an object on the basis of previously isolated abstractions.

Concretization, aimed at reproducing the development of an object as an integral system, becomes a special research method. Thinking from selected individual abstractions concentrates the whole object. The result is concrete, but already mentally concrete (in contrast to the real concrete, which exists in reality).

The unity of diversity, the combination of many properties and qualities of an object, is called concrete here.

Abstract, on the contrary, is one-sided, isolated from other moments of development, the properties or characteristics of a given object.

A special method of theoretical knowledge is method of ascending from the abstract to the concrete, aimed at reproducing development and its sources.

It is necessary both for the knowledge of complex processes, and for such a presentation of the results of knowledge, which would most adequately reproduce the development and functioning of complex objects.

3. Simulation- a method of studying objects of knowledge on their models. It involves the construction and study of models of real-life objects and phenomena.

The need for modeling arises when the study of the object itself is impossible, difficult, expensive, takes too long, etc.

There must be a known similarity (similarity relation) between the model and the original: physical characteristics, functions; the behavior of the object under study and its mathematical description; structures, etc. It is this similarity that allows you to transfer the information obtained as a result of the study of the model to the original.

Depending on the nature of the models used in scientific research, several types of modeling are distinguished.

1. Physical(material, subject): characterized by a physical similarity between the model and the original, its goal is to reproduce in the model the processes inherent in the original. According to the results of the study of certain physical properties of the model, the phenomena occurring in natural (“natural”) conditions are judged. Neglecting the results of such simulations can have serious consequences. An example is the story of the English battleship Captain, built in 1870. Shipbuilding scientist W. Reed examined the ship model and revealed serious defects in its design. He reported this to the Admiralty, but his opinion was not taken into account. As a result, the ship capsized when going to sea, which resulted in the death of more than 500 sailors.

At present, physical modeling is widely used for the development and experimental study of various structures (power plant dams, irrigation systems, etc.), machines, etc. before they are actually built. For example, the aerodynamic qualities of aircraft are studied on models.

2. Perfect(mental): this type of M. includes a variety of mental representations in the form of certain imaginary models. Models appear in the form of diagrams, graphs, drawings, formulas, systems of equations, etc.

For example, Rutherford's model of the atom resembled the solar system: electrons ("planets") revolve around the nucleus ("Sun"). The same model can be realized materially in the form of sensually perceived physical models.

Ideal modeling includes the so-called “mental modeling”, which is classified into (see table 1):

1) visual modeling is made on the basis of the researcher's ideas about a real object by creating a visual model that displays the phenomena and processes occurring in the object
Hypothetical- a hypothesis is laid about the patterns of processes in a real object, which reflects the level of knowledge of the researcher about the object and is based on cause-and-effect relationships between the input and output of the object under study	analog is based on the use of analogies of various levels, the analog model reflects several or only one side of the functioning of the object	Modeled associated with the creation of a mock-up of a real object at a certain scale and its study
2) symbolic modeling it is an artificial process of creating a logical object that replaces the real one and expresses its main properties using a certain system of signs and symbols. Depending on the semantic units used, it is divided into
linguistic (descriptive)	sign (graphic)
3) mathematical modeling based on the description of a real object using a mathematical apparatus

The complexity, inexhaustibility, infinity of the object of study in social work forces us to look for simpler analogues for research in order to penetrate into its essence, into its internal structure and dynamics. An object that is simpler in structure and accessible to study becomes a model of a more complex object, called a prototype (original). It opens up the possibility of transferring the information obtained when using the model, by analogy with the prototype. This is the essence of one of the specific methods of the theoretical level - the modeling method.

The modeling method is constantly evolving; some types of models are being replaced by others as science progresses. At the same time, one thing remains unchanged: the importance, relevance, and sometimes the indispensability of modeling as a method of scientific knowledge.

4. A special kind of modeling based on abstraction is thought experiment.

In such an experiment, the researcher, on the basis of theoretical knowledge about the objective world and empirical data, creates ideal objects, correlates them in a certain dynamic model, mentally imitating the movement and those situations that could be in real experimentation. At the same time, ideal models and objects help in a “pure” form to identify the most important, essential connections and relationships for the cognizer, to play the designed situations, to weed out ineffective or too risky options.

5. Induction (lat. - guidance) - a logical method (reception) of research associated with the generalization of the results of observations and experiments and the movement of thought from the individual to the general.

In I., the data of experience “lead” to the general, induce it. Since experience is always infinite and incomplete, inductive conclusions always have a problematic (probabilistic) character. Inductive generalizations are usually viewed as empirical truths or empirical laws.

In the dictionary of the Russian language, induction is understood as a way of reasoning from particular facts, provisions to general conclusions.

Valery Pavlovich Kokhanovsky highlights the following types of inductive generalizations:

1) popular induction, when regularly repeating properties observed in some representatives of the studied set (class) and fixed in the premises of inductive reasoning are transferred to all representatives of the studied set (class) - including its unexplored parts.

So, what is true in "n" observed cases is true in the next, or in all observed cases similar to them. However, the resulting conclusion often turns out to be false (for example, “all swans are white”) due to hasty generalization. Thus, this kind of inductive generalization exists until a case is encountered that contradicts it (for example, the fact that there are black swans). Popular induction is often called case enumeration induction.

That is, when the number of cases is not limited, almost infinite, we are dealing with incomplete induction. This procedure of establishing a general proposition based on several separate cases in which a certain property was observed, which is characteristic of all possible cases similar to the observed one, is called induction by simple enumeration.

The main problem of complete induction is the question of how legitimate is such a transfer of knowledge from individual cases known to us, listed in separate sentences, to all possible and even cases still unknown to us.

2) Induction incomplete– where it is concluded that all representatives of the set under study have the property “n” on the basis that “n” belongs to some representatives of this set.

For example, Some metals have the property of electrical conductivity, which means that all metals are electrically conductive.

3) full induction, which concludes that all representatives of the studied set have the property “n” on the basis of the information obtained during the experimental study that each representative of the studied set has the property “n”.

Those. the general sentence is established by enumerating in the form of singular sentences all the cases that are subsumed under it. If we have been able to enumerate all cases, and this is the case when the number of cases is limited, then we are dealing with complete induction.

When considering complete induction, it must be borne in mind that it does not give new knowledge and does not go beyond what is contained in its premises. The general conclusion obtained on the basis of the study of particular cases summarizes the information contained in them, allows you to generalize, systematize it.

4) Scientific induction, in which, in addition to the formal substantiation of the generalization obtained by induction, a substantive additional substantiation of its truth is given, including with the help of deduction (theories, laws). Scientific induction gives a reliable conclusion due to the fact that here the emphasis is on necessary, regular and causal relationships.

In any scientific research, it is often important to establish causal relationships between various objects and phenomena. For this, appropriate methods based on inductive reasoning are used.

Consider the main inductive methods for establishing causal relationships(Bacon–Mill rules of inductive research).

a) Single Similarity Method: if the observed cases of a phenomenon have only one circumstance in common, then, obviously (probably), it is the cause of this phenomenon.

b) Single difference method: if the cases in which the phenomenon occurs or does not occur differ only in one antecedent circumstance, and all other circumstances are identical, then this one circumstance is the cause of this phenomenon

in) Combined Similarity and Difference Method is formed as a confirmation of the result obtained using the single similarity method by applying the single difference method to it: this is a combination of the first two methods.

G) Accompanying change method: if a change in one circumstance always causes a change in another, then the first circumstance is the cause of the second. At the same time, the rest of the previous phenomena remain unchanged.

The considered methods of establishing causal relationships are most often used not in isolation, but in interconnection, complementing each other.

Deduction (lat. - derivation):

- firstly, the transition in the process of cognition from the general to the individual (private), the derivation of the individual from the general;

- secondly, the process of logical inference, i.e., the transition according to certain rules of logic from some given sentences - premises to their consequences (conclusions). As one of the methods (techniques) of scientific knowledge is closely related to induction. These are, as it were, dialectically interconnected ways of thought movement. V.P. Kokhanovsky believes that great discoveries, leaps forward in scientific thought are created by induction, a risky but truly creative method. D. prevents the imagination from falling into error, it allows, after the establishment of new starting points by induction, to deduce consequences and compare conclusions with facts. D. provides a test of hypotheses and serve as a valuable antidote to the excess of fantasy.

The term "deduction" appeared in the Middle Ages and was introduced by Boethius. But the concept of deduction as a proof of a sentence by means of a syllogism appears already in Aristotle (First Analytics). An example of deduction as a syllogism would be the following conclusion.

The first premise: crucian is a fish;

second premise: crucian carp lives in water;

conclusion (conclusion): fish lives in water.

7. Formalization - a special approach in scientific knowledge, which consists in the use of special symbols that allow one to abstract from the study of real objects, from the content of the theoretical positions that describe them, and instead operate with a certain set of symbols (signs). Example F. - mathematical description. To build any formal system, it is necessary:

1) setting the alphabet, i.e. a certain set of characters;

2) setting the rules by which "words", "formulas" can be obtained from the initial characters of this alphabet;

3) setting the rules by which one can move from one word, formula of a given system to other words and formulas (the so-called inference rules).

Dignity F. - provides brevity and clarity of recording scientific information. A formalized language is not as rich and flexible as a natural one, but it is not polysemantic (polysemy), but has unambiguous semantics. Thus, a formalized language has the monosemic property.

The language of modern science differs significantly from natural human language. It contains many special terms, expressions, formalization tools are widely used in it, among which the central place belongs to mathematical formalization. Based on the needs of science, various artificial languages ​​\u200b\u200bare created to solve certain problems. The entire set of created and being created artificial formalized languages ​​is included in the language of science, forming a powerful means of scientific knowledge.

7 . In scientific knowledge hypothetical-deductive method was developed in the 17-18 centuries, when significant progress was made in the field of mechanics of terrestrial and celestial bodies. The first attempts to use this method in mechanics were made by Galileo and Newton. Newton's work "The Mathematical Principles of Natural Philosophy" can be considered as a hypothetical-deductive system of mechanics, the premises of which are the basic laws of motion. The method of principles created by Newton had a great influence on the development of exact natural science.

From a logical point of view, a hypothetical-deductive system is a hierarchy of hypotheses, the degree of abstraction and generality of which increases as they move away from the empirical basis. At the very top are the hypotheses that have the most general character and therefore have the greatest logical force. Hypotheses of a lower level are derived from them as premises. At the lowest level of the system are hypotheses that can be compared with empirical reality.

A variation of the hypothetical-deductive method can be considered a mathematical hypothesis, which is used as the most important heuristic tool for discovering patterns in natural science. Usually, hypotheses here are some equations that represent a modification of previously known and verified relationships. By changing these ratios, they make up a new equation expressing a hypothesis that refers to unexplored phenomena. In the process of scientific research, the most difficult task is to discover and formulate those principles and hypotheses that serve as the basis for all further conclusions. The hypothetical-deductive method plays an auxiliary role in this process, since it does not put forward new hypotheses, but only checks the consequences arising from them, which thereby control the research process.

8. Close to the hypothetical-deductive method axiomatic method. This is a way of constructing a scientific theory, in which it is based on some initial provisions (judgments) - axioms, or postulates, from which all other statements of this theory must be derived in a purely logical way, through proof. The construction of science on the basis of the axiomatic method is usually called deductive. All concepts of the deductive theory (except for a fixed number of initial ones) are introduced by means of definitions formed from a number of previously introduced concepts. To one degree or another, deductive proofs characteristic of the axiomatic method are accepted in many sciences, but the main area of ​​its application is mathematics, logic, and also some branches of physics.

All the methods of cognition described above in real scientific research always work in interaction. Their specific systemic organization is determined by the characteristics of the object under study, as well as the specifics of a particular stage of the study.

As already noted, these methods are direct manifestations of social dialectics, or dialectics social cognition. They're called general scientific because they are used in the knowledge of all phenomena of reality, therefore, in all sciences, including political science.

These methods have been formed in the course of centuries of human cognitive activity and are being improved in the process of its development.

It should be said that general scientific methods, being methods of cognition of reality , are simultaneously researchers' thinking methods ; on the other hand, the methods of thinking of researchers act as methods of their cognitive activity.

Let's give a brief description basic general scientific methods for studying political phenomena and processes.

Analysis and synthesis

In the study of political problems, scientists subject them to scientific analysis , i.e. mental division of political phenomena into their elements , to explore each one. But any of these elements functions only in interconnection and interaction with other elements. Therefore, the analysis of elements involves simultaneously understanding their relationships and interactions , which is the content synthesis.

Thus, analysis and synthesis are two interrelated aspects of people's mental activity and, accordingly, two interrelated methods of cognizing reality, in this case political.

When analyzing political phenomena, the specific features of their elements and their role in the functioning of these phenomena are comprehended. In the course of scientific synthesis, a holistic view of these phenomena, their content and development laws is formed.

In the process of analytical and synthesizing activity of thinking, a transition is made from the initial speculative (and therefore superficial) judgments about the studied political phenomena to more or less deep and holistic ideas about them. The emergence of new knowledge about them indicates the creative (heuristic) nature of analysis and synthesis.

Inductive and deductive methods of cognition

Inductive method (induction ), used in political research, is a way of understanding political phenomena, going from the recording of experimental (empirical) data and their analysis to their systematization, generalizations and general conclusions drawn on this basis. This method also consists in the transition from some ideas about certain political phenomena and processes to others - more general and most often deeper. The basis of the functioning of the inductive method of cognition in all cases are empirical (experimental) data.

However, inductive generalizations will be completely flawless only if all the scientifically established facts on the basis of which these generalizations are made are thoroughly studied. It is called complete induction. But most often it is very difficult to do this, and sometimes impossible.

Therefore, in cognitive activity, including the study of political phenomena and processes, the method is used incomplete induction: the study of some part of the studied phenomena and the extension of the conclusion to all phenomena of a given class. Generalizations obtained on the basis of incomplete induction, in some cases, may be quite definite and reliable, in others - more probabilistic.

The validity of inductive generalizations can be tested by applying deductive research method. Its essence lies in the derivation from any general provisions that are considered reliable, certain consequences, some of which can be verified empirically. If the consequences arising from inductive generalizations are confirmed by practical experience (experiment or real political processes), then these generalizations can be considered reliable, i.e. corresponding to reality.

Analogy

This is a certain kind of comparison of phenomena and processes, including those occurring in the political life of society: having established the similarity of some properties of certain political phenomena (processes), a conclusion is made about the similarity of their other properties. At the same time, it is necessary to take into account the specific features of the development of political phenomena. It is not necessary to reduce their study only to the search for analogies. In addition, the analogy method is most often used along with other general scientific methods. At the same time, the scientific efficiency of using the analogy method is quite high.

Modeling

This is a reproduction in a specially created object (model) of the properties of the phenomenon under study, including the political one. The application of this method is, as a rule, creative in nature, opening up something new. In particular, when analyzing the model itself, properties are found that are absent in its individual parts and their simple sum. This is the effect of the principle: "The whole is greater than the sum of its parts." The knowledge gained about a political phenomenon or process as a whole is used for their further study.

When studying the processes of social life, including political ones, the so-called causal models. They help to reveal objective causal relationships and interdependencies between social phenomena, the generation of some of them by others, as well as the emergence of new properties in them. However, such models do not always make it possible to draw conclusions about the phenomenon under study as a whole, since, revealing its objective aspects, they do not fix subjective factors relating to the consciousness of people whose actions directly determine the content and direction of any social phenomena and processes.

This difficulty is resolved by political scientists in the following way: when analyzing the political processes taking place throughout society, i.e. at the macro level, cause-and-effect models are used that reveal the objective factors of people's activity and behavior, and when analyzing the processes occurring in individual teams, i.e. at the micro level, along with cause-and-effect, so-called cognitive models of interactions between individuals are used, with the help of which the motives, beliefs and goals of the subjects of political activity are revealed.

Learning about systems and using that knowledge to create and manage systems requires systems thinking, consisting in a combination of analytical and synthetic ways of thinking. essence analysis consists in dividing the whole into parts, in representing the complex as a set of simpler components. But in order to cognize the whole, the complex, the reverse process is also necessary - synthesis . The need to combine these types of cognition follows from the property of the emergence of systems: the integrity of the system is violated during analysis, when the system is divided, not only the essential properties of the system itself are lost, but also the properties of its parts that are separated from it. The result of the analysis is only the disclosure of the composition of the components, the knowledge of how the system works, but not the understanding of why and why it does this. Synthetic thinking explains the behavior of the system, why the system works the way it does. At the same time, the system should be considered as part of a larger whole.

Analysis and synthesis complement each other. So, when synthesizing an organizational structure, it is necessary to first analyze the activities of the organization being created, single out individual processes (functions), compare organizational units with them, and then combine them into a separate whole, i.e. carry out the synthesis. When choosing a method of functioning of an organization, the opposite often takes place: first, a synthetic approach is used - the activity of the organization as a whole is considered; a common goal and mode of functioning are selected, and then the selected mode is disaggregated into separate functions.

The main content of the "Systems Analysis" discipline is complex decision-making problems, in the study of which informal procedures for presenting common sense and ways of describing situations play no less a role than formal mathematical apparatus. System analysis is a synthetic discipline. It can be divided into three main directions. These three directions correspond to three stages that are always present in the study of complex systems:

1) building a model of the object under study;

2) setting the research problem;

3) solution of the set mathematical problem.

The knowledge of systems and the use of this knowledge to create systems and control them is carried out through modeling.

The ultimate goal of system analysis is to resolve the problem situation that has arisen before the object of the ongoing system research (usually it is a specific organization, team, enterprise, separate region, social structure, etc.). System analysis deals with the study of a problem situation, clarification of its causes, development of options for its elimination, decision-making and organization of the further functioning of the system, resolving the problem situation. The initial stage of any system research is the study of the object of the ongoing system analysis, followed by its formalization. At this stage, tasks arise that fundamentally distinguish the methodology of system research from the methodology of other disciplines, namely, a two-pronged task is solved in system analysis. On the one hand, it is necessary to formalize the object of system research, on the other hand, the process of studying the system, the process of formulating and solving the problem, is subject to formalization.

Let's take an example from systems design theory. The modern theory of designing complex systems can be considered as one of the parts of systems research. According to her, the problem of designing complex systems has two aspects. First, it is required to carry out a formalized description of the design object. Moreover, at this stage, the tasks of a formalized description of both the static component of the system (mainly its structural organization is subject to formalization) and its behavior in time (dynamic aspects that reflect its functioning) are solved. Secondly, it is required to formalize the design process. The components of the design process are the methods of forming various design solutions, methods of their engineering analysis and decision-making methods for choosing the best options for implementing the system.

We will try to outline the main procedures of the algorithm for conducting a system analysis, which are a generalization of the sequence of stages for conducting such an analysis, formulated by a number of authors, and reflect its general patterns. We list the main procedures for system analysis:

- study of the structure of the system, analysis of its components, identification of relationships between individual elements;

- collection of data on the functioning of the system, the study of information flows, observations and experiments on the analyzed system;

– building models;

– verification of the adequacy of models, analysis of uncertainty and sensitivity;

– study of resource opportunities;

– determination of the goals of system analysis;

– formation of criteria;

– generation of alternatives;

– implementation of choice and decision-making;

– implementation of the results of the analysis.

The concept of a model

Replacing one object with another in order to obtain information about the most important properties of the original object using the model object can be called modeling, i.e. modeling is the representation of an object by a model to obtain information about the object by conducting an experiment with its model.

From the point of view of philosophy, modeling should be considered as an effective means of understanding nature. At the same time, the modeling process assumes the presence of an object of study, a researcher-experimenter and a model.

In automated information processing and control systems, the object of modeling can be production and technological processes for obtaining final products; the processes of movement of documents, information flows in the implementation of the institutional activities of the organization; processes of functioning of a complex of technical means; processes of organization and functioning of information support of automated control systems; processes of functioning of the ACS software.

The advantages of modeling are that it becomes possible by relatively simple means to study the properties of the system, change its parameters, and introduce the target and resource characteristics of the external environment. As a rule, modeling is used in the following stages:

1) studies of the system before it is designed, in order to determine its main characteristics and rules for the interaction of elements among themselves and with the external environment;

2) designing a system for the analysis and synthesis of various types of structures and choosing the best implementation option, taking into account the formulated optimality criteria and limitations;

3) operation of the system to obtain optimal modes of operation and predictable estimates of its development.

At the same time, the same system can be described by different types of models. For example, the transport network of a certain area can be modeled by an electrical circuit, a hydraulic system, a mathematical model using the apparatus of graph theory.

The following types of models are widely used to study systems: physical (geometric similarity, electrical, mechanical, etc.) and symbolic (meaningful and mathematical). A mathematical model is understood as a set of mathematical expressions that describe the behavior (structure) of the system and the conditions (perturbations, restrictions) in which it operates. In turn, mathematical models, depending on the mathematical apparatus used, are divided, for example, into:

· static and dynamic;

deterministic and probabilistic;

discrete and continuous;

analytical and numerical.

Static models describe an object at any point in time, while dynamic models reflect the behavior of an object over time. Deterministic models describe processes in which there are no (not taken into account) random factors, and probabilistic models reflect random processes - events. Discrete models characterize the processes described by discrete variables, continuous - continuous. Analytical models describe the process in the form of certain functional relationships and/or logical conditions. Numerical models reflect the elementary stages of calculations and the sequence of their implementation. If natural language (the language of communication between people) is used to describe the system, then such a description is called a content model. Examples of meaningful models are: verbal problem statements, systems development programs and plans, organization goal trees, etc. Content models are of independent value in solving problems of research and systems management, and are also used as a preliminary step in the development of mathematical models. Therefore, the quality of the mathematical model depends on the quality of the corresponding mathematical model.

Natural language (the language of communication between people), diagrams, tables, flowcharts, graphs are used as language means for describing meaningful (verbal) models. Complex systems are called complex because they are difficult to formalize. For them, it is advisable to use meaningful models. Content models are indispensable in the early stages of complex system design, when the concept of the system is being formed. System analysis methods using decomposition approach, allow you to identify an ordered set of subsystems, elements, system properties and their relationships. The integrated content model of the system allows you to present the big picture, make a generalized description, in which the main entities are emphasized, and the details are hidden. The main thing in such a model is brevity and clarity. Such a model can serve as a basis for building more detailed models that describe individual aspects, subsystems. Thus, a meaningful model can serve as a framework for constructing other models, including mathematical ones. It also serves to structure information about an object.

The multiplicity of models of one object is due, in particular, to the fact that for different purposes it is required to build (use) different models. One of the bases for the classification of models can be the correlation of types of models with types of goals. For example, models can be divided into cognitive and pragmatic.

Cognitive models are a form of organization and presentation of knowledge, a means of connecting new knowledge with existing ones. Therefore, when a discrepancy between the model and reality is detected, the task is to eliminate this discrepancy by changing the model by bringing the model closer to reality.

Pragmatic models are a means of management, a means of organizing practical actions, a way of presenting exemplary correct actions or their results. Therefore, when a discrepancy is found between the model and reality, the task is to eliminate this discrepancy by changing reality in such a way as to bring it closer to the model.

Thus, pragmatic models are of a normative nature, they play the role of a standard, a model, under which both the activity itself and its result are “adjusted”. Examples of pragmatic models are plans, action programs, organizational charters, codes of laws, algorithms, working drawings and templates, selection parameters, technological tolerances, examination requirements, etc.

There are physical and abstract models.

Physical models are formed from a set of material objects. For their construction, various physical properties of objects are used, and the nature of the material elements used in the model is not necessarily the same as in the object under study. An example of a physical model is a layout.

Information (abstract) model is a description of the object of research in any language. The abstractness of the model is manifested in the fact that its components are concepts, and not physical elements (for example, verbal descriptions, drawings, diagrams, graphs, tables, algorithms or programs, mathematical descriptions).

Information Models describe the behavior of the original object, but do not copy it. An information model is a purposefully selected information about an object that reflects the most significant properties of this object for the researcher. Among the information (abstract) models, there are: - descriptive, visual and mixed; - epistemological, infological, cybernetic, sensual (sensual), conceptual, mathematical.

Gnoseological models aimed at studying the objective laws of nature (for example, models of the solar system, biosphere, world ocean, catastrophic natural phenomena).

infological model (narrow interpretation) is a parametric representation of the process of information circulation, subject to automated processing.

Sensual Models- models of some feelings, emotions, or models that affect human feelings (for example, music, painting, poetry).

conceptual model- this is an abstract model that reveals the cause-and-effect relationships inherent in the object under study and significant within the framework of a particular study. The main purpose of the conceptual model is to identify a set of cause-and-effect relationships that must be taken into account to obtain the required results. The same object can be represented by different conceptual models, which are built depending on the purpose of the study. So, one conceptual model can display the temporal aspects of the system functioning, another - the impact of failures on the system performance.

Mathematical model is an abstract model presented in the language of mathematical relations. It takes the form of functional dependencies between the parameters taken into account by the corresponding conceptual model. These dependencies specify the cause-and-effect relationships identified in the conceptual model and characterize them quantitatively.

Thus, model is a special object that in some respects replaces the original. Fundamentally, there is no model that would be a complete equivalent of the original. Any model reflects only some aspects of the original. Therefore, in order to obtain large gaps about the original, it is necessary to use a set of models. The complexity of modeling as a process lies in the appropriate choice of such a set of models that replace the real device or object in the required respects. For example, a system of differential equations that describes switching processes in the elements of a digital device can be used to evaluate their performance (switching time), but it is inappropriate to use to build tests or timing diagrams of the device. Obviously, in the latter cases it is necessary to use some other models, for example, logical equations