Позитивные изменения. Том 2, № 3 (2022). Positive changes. Volume 2, Issue 3 (2022) - Редакция журнала «Позитивные изменения»

identify key properties of the social entrepreneur’s image in Russia, Kazakhstan and Belarus, and to determine the differences between them in each of these countries.

To conduct a comparative analysis of images, we use the psychosemantic approach. Psychosemantic methods are effective in studying people’s perceptions of an object. In particular, for recreating the framework of categories that define the public perception of social entrepreneurs. Multidimensional assessment methods developed within the framework of psychosemantics enable us to differentiate between the perception of a social entrepreneur in his/her home country and in other countries. The respondents are asked to rate the social entrepreneur’s image by key factors reflecting a range of the most important properties, such as social effect, financial stability, motivational properties, dependence on external resources, and others.

This approach has long been used in political psychology research (in particular, to describe images of political leaders, countries, gender researchers and many others). It is also actively used in ethnic psychology, social communication psychology, and arts psychology (Petrenko, Mitina & Berdnikov, 2002; Petrenko & Mitina, 2000; Petrenko, 2005).

RESEARCH METHODOLOGY

Experimental psychosemantics is a relatively new field of Russian psychology. This approach uses the methodology of constructing subjective semantic spaces as operational models of categorial structures of individual and social perception and is intended to recreate the image of the world in different areas of human life. The task of psychosemantics involves reconstructing the individual system of meanings through which the subject perceives the world, other people, himself, genesis, as well as the systemic functioning of all these objects.

The experimental paradigm of psychosemantics derives from C. Osgood’s method of constructing semantic spaces (Osgood, C. E., Suci, G. J., & Tannenbaum, P. H., 1957) (semantic differential) and G. Kelly’s theory of personal constructs (repertory grid technique) (Kelly, G., 1955). It includes multidimensional statistical methods for revealing the categorial structure of the subject’s perception. Russian psychosemantics is based on the methodology employed by the schools of L. Vygotsky, A. Leontiev, A. Luria, S. Rubinstein, and is related to the problem of the formation of everyday social perception. While being a psychological discipline, psychosemantics nevertheless has a clear interdisciplinary character, connected with philosophy and sociology.

Psychosemantic approach is peculiar in that it is based on analyzing the categorial structures of the perception and the development of a system of meanings through which the subject perceives the world. The subject classifies, evaluates or scales objects observed, makes judgments about similarities and differences between objects, etc. The revealed structures inherent in the data matrix are interpreted as categorial structures of the subject’s perception. The application of multivariate statistical methods makes it possible to identify these structures and facilitates their further interpretation. For example, factor analysis makes it possible to identify “bundles” of interrelated features, constructs, and thus bring the initial basis of descriptive features down to certain generalized categories — the factors that make up the coordinate axes of the semantic space. The factor loadings of each descriptive characteristic show the degree to which a given constituent aspect is expressed in that property and how it corresponds geometrically to its projection on the factor axis. In mathematical terms, constructing a semantic space means reducing large dimensions (traits, scales, descriptors) to smaller ones, formed by categories of factors. Semantically, factor categories represent a certain meta-language that is necessary to describe meanings, so semantic spaces allow us to assign values to a fixed alphabet of factor categories, perform semantic analysis of these values, make judgments about their similarity or difference, and calculate semantic proximity between different values by calculating the distance between corresponding coordinate points in n-dimensional space.

To use the psychosemantic approach to building a social entrepreneur’s image, we developed a list of 38 characteristics[41]. These characteristics were presented as statements. For example, “He/ she believes that the state must assist his/her development,” “Competitive,” “Offers an innovative solution to a social problem,” “Can hardly be called a happy person,” etc. The respondents were asked to rate each statement on a scale of 1 to 5 based on their perceived relevance of that statement to a specific object of study. The list of objects to be evaluated includes 4 items for each country:

1. “The Social Entrepreneur in his/her home country”;

2. “The Social Entrepreneur in the United States”;

3. “The Social Entrepreneur under “perfect conditions”;

4. “Social Entrepreneur in Russia” — for respondents from Kazakhstan and Belarus, and “Social Entrepreneur in Kazakhstan” — for respondents from Russia.

Participants of the SAP UP 2017 contest were chosen as the respondents for the study. Filling out the research questionnaire was part of the application process. Based on the responses, we can say that all respondents identify themselves as social entrepreneurs. The sample size was 323 respondents: 105 from Belarus, 91 from Kazakhstan, and 127 from Russia.

Of the total number of protocols for each country (see Table 1), we excluded those in which respondents used one response category in more than 90 % of the answers. In other words, if the respondent rated one object with 38 points and distributes the remaining 4 points among other categories, such questionnaires would be excluded from the study. Table 1 shows the number of protocols completed correctly for each sample in each country.

An exploratory factor analysis using the principal component method was used for statistical analysis of the data. Rotation method: Oblimin rotation with Kaiser normalization.

Table 1. Total sample composition and number of “correct” protocols

Table 2. Breakdown of respondents by age[42]

OUTCOMES

The first stage was to analyze the factor structures in the perception of the image of a social entrepreneur in his/her home country and in other countries. The analysis was conducted in each sample population.

Based on the analysis, we can distinguish four main factors in the final matrix for assessing the image of a social entrepreneur. While the descriptions of these factors have some nuances, in general respondents from