Home – Home – Jornals – Philosophy of Sciences 2025 number 1

The article analyzes the concepts of surveyability and rigor of mathematical proof. It is shown that surveyability and rigor can be considered contextually. These concepts are considered in the context of mathematical practice. Several examples from the history of mathematics reveal the contextual nature of the concept of rigor. It is shown that the concept of rigor can be considered similar to the concept of surveyability. Distinguishing of mesoscopic surveyability suggests the possible distinguishing of an intermediate concept of rigor in addition to global and local rigor.,

The paper comprehends the problem of the free will in terms of determinism and demonstrates the consistency of Laplace's demon in the context of predicting the dynamics of the states of systems with complex behavior using the example of cellular automata

In the philosophy of biology, the concept “measure of life” describes the phenomenon of life in its qualitative and quantitative integrity. This integrity is the result of the optimization of biosystems, wherein top-down causation, i.e. the determination of lower-level instances by higher-level variables, is actualized. In its initial forms, top-down causation is constrained in its scope, integrating only select aspects of life, either quantitative aspects (adaptive control) or qualitative aspects (feedback control). As biosystems evolve, the forms of downward causality become more complex (adaptive information control), which enables combining both the quality and quantity of life into the category of measure. The development of control mechanisms in biosystems allows for flexible behavior in accordance with environmental demands and the formation of new goals to achieve outcomes beneficial for the organism.,

Since the dawn of pharmacotherapy, one of the main questions has been which drug is effective for treating a particular disease. Researchers agree that the formation of experimental foundations for testing the effectiveness of drugs dates back to the period of the scientific revolution of the 17th century, when James Lind carried out an experiment on treating scurvy with citrus fruits, and the first clinical trial conducted according to the canons of modern evidence-based medicine dates back to 1948. The article provides a retrospective analysis of some pharmacotherapy practices that preceded this period in order to trace the development of clinical trial methodology from stochastic practices to meaningful scientific decisions that resulted in the formation of a modern paradigm of biomedical experiments involving of humans as subjects. The relevance of the study is based on the identification and description of the main stages in the development of the study of pharmacotherapy practices, which is why this review seems important for further study of the history of clinical trials.,

The article reveals aspects of simple, fundamental and contextual demarcation and the related understanding of the boundary and cross-boundary nature of the scientific field, their weaknesses and difficulties in applying them to the current reality of science. The author presents pluralistic demarcation, in particular the cluster approach of M. Mahner and D. Fernandez-Beanato, as the most effective for solving the problem of establishing the boundaries of science. Changes in the implementation of demarcation procedures lead to an understanding of the transboundary nature of science. Transboundarity is defined as a phenomenon with a complex structure including interconnected grounds (geographical, historical, functional, and political). It is most clearly expressed in the context of digitalization, when political and geographical limits are technically leveled. Transboundary science is a field of cooperation, a field of conflict and a field of emergence of new boundaries and areas of knowledge. In this case, the boundary is understood as a social construct that forms ideas about the stable identification of science, stable relations within the scientific community, and the priority of scientific truth in the perception of practitioners (scientists) and society. The author concludes that the development of provisions for transboundary science is becoming relevant in the current agenda.,

The paper aims to offer an analysis and specification of time, temporariness and transience within narrative and narrative research. Despite the substantive variety and methodological diversity of narrative research, the temporal order is recognized as its fundamental criterion. On the one hand, time specifies narrative and allows differentiating narrative from other types of discourse; on the other hand, it performs referential (communicative) and evaluative functions. In contrast to the Eurocentric and logocentric understanding of time, P. Ricoeur justifies the need to consider chronological (“episodic”, “hourly”) and non-chronological times, since it is the latter that plays a crucial role in the narration of the experience of the past. The result of this approach is the division of time: the time of past events, the time of narrative telling, and the time defined by the final event. The complication of time also occurs in terms of frequency, duration and order. The example of the analysis of “turning events” shows that it is the “configuration of time” that recontextualizes the experience of the past in terms of its consequences, which is true for both personally significant and collective narratives.,

The purpose of the article is to understand the results of the digitalization of science and to find answers to the question: is the digitalization of science limited to changes in the methods of recording and transmitting information, or does it lead to a fundamental modification of the cognitive and social aspects of scientific activity? The methodological framework of the study contains two explanatory schemes - externalism and internalism, as well as the position of epistemological constructivism. The results of the study can be summarized as follows. Digitalization gives rise to new means of scientific communication - digital platforms. The platformization of science entails changes in the social forms of existence of science, turning digital platforms into elements of the institutional structure of the scientific community, into social institutions through which the scientific community and society as a whole interact. Within the framework of digital platforms, specific institutional norms of scientific activity are formed and a new image of a scientist is crystallized, including a digital scientist, a data scientist, and a scientific blogger. In line with digitalization, there is a tendency to rethink the current scientific picture of the world; the idea of the Universe as computable information or as a giant quantum computer appears. Digitalization contributes to the formation of a new understanding of the objectivity of scientific knowledge as interobjectivity resulted from the transformation of digital technologies and tools into full-fledged participants in cognitive activity. It actualizes new epistemologies, namely “ethistemology of big data”, which absolutizes the methodology of big data, and “epistemology of domains”, which combines traditional methods of scientific research and the methodology of big data. The conclusion is the following: digitalization entails a fundamental transformation of scientific thinking and scientific activity.,

The article aims to develop an approach to the theoretical justification of the use of machine learning (ML) methods in natural sciences. The main obstacle on this path is the problem of the “black box”, or “epistemic opacity”, which is the lack of access to all elements of the cognitive process carried out through ML. In developing the approach, the authors formulate a criterion that must be met to solve the problem. The authors point out that the reason for turning to machine learning in natural sciences is the limited applicability of traditional analytical and qualitative methods for studying nature, since human thinking has reached its limits in their use - because of the complexity and multidimensionality of the studied systems. Therefore, the solution to the “black box” problem must explain how ML can overcome these limits, i.e. how human thinking can access a domain of knowledge that is inaccessible to it due to its own internal limitations. In this regard, it is argued that the approach that spontaneously formed within computer science cannot serve as a basis for solving this task. Such an approach involves incorporating existing scientific knowledge into ML tools in order to fight against bias, which is characteristic of machine learning, i.e. the researcher’s subjective assumptions that are necessary for successful generalization beyond the training set. The authors show that incorporating scientific knowledge into ML tools has only applied value and does not solve the problem of theoretical justification, since it does not meet the criterion they propose - it does not overcome the limits of human thinking, but merely aligns ML results with existing scientific knowledge.,

This work is a natural extension of the previous study which the authors undertook in relation to the problem of digital transformation of organizations and outlined in the first part of the article. Unlike the first part, here the main focus is on presenting the results of the analysis of the problem of digital transformation of the subject component of economic actors. In addition, the results of the analysis of what organizational order currently exist in organizations, how and with what tools their digital transformation is carried out, why they are not adequate to the new organizational order, where everything is going and what everything can come to will also be presented. Note that the numbering of sections, figures and tables in this work continues the numbering in the first part of the article. Subsequent works of the cycle of articles planned by the authors will discuss the methodological and technological issues of the proposed approach to the digital transformation of the subjects of economic actor management.,