Problem of forming expert groups in regions with different levels of socio-cultural development

The research focuses on the process of expert group formation in the context of the implementation of “breakthrough” national projects and programs for the territories’ modernization and management in the regions. According to the developers, they should be realized through specific strategic measures with broad involvement of target groups to ensure the most balanced and effective socio-economic and socio-cultural modernization of the regions.

The relevance of studying this phenomenon is due to a number of reasons, but the main thing is the fact that at present, scientifically-based (rational) procedures for identifying and selecting target groups of experts-stakeholders are not used in the management practice. Based on this, we can make an assumption about the deformation of the processes of forming decision groups. The deformation leads to the alienation of a large number of interested citizens, potential experts from the procedures for the development and implementation of program activities within the framework of national projects and programs for the management modernization. This can be traced in modern works devoted to the problem analysis of public participation in national projects at the regional and municipal levels [1; 2], and information and organizational support for their implementation [3]. Currently, we are faced with the practical and scientific-methodological problem of selecting stakeholders as participants in expert groups for making management decisions.

This context maintains the purpose of our research. This purpose is related to the definition of the structures of real expert groups of decisionmaking, as well as latent experts through the establishment of their socio-managerial features and qualitative characteristics.

Conceptual foundations

We believe that groups consisting of various social agents (subjects) can participate in the implementation of national projects and programs for the regions’ modernization. The latter may differ in their characteristics and functionality, but at the same time, demonstrate common socio-economic, socio-political, and socio-professional positions. We distinguish three types of such groups.

• A)    The first type is real groups that are able to implement projects and programs for the region’s development. These effective groups represent government bodies, labor collectives, various types of public organizations, business structures, etc. E. Mayo studied such types of groups in the framework of the Hawthorne experiment [4].

• B)    The second type is various associative communication groups that form public opinion. They were studied in one form or another by G.P. Schedrovitsky [5], P. Bourdieu [6], and a

team led by A.V. Tikhonov [7], who diagnosed the public support degree for the ability of the power and management vertical to successfully perform its functions within the framework of a longitudinal study.

• C)    The third type is expert groups that analyze technical, economic, and socio-cultural characteristics of the regions, and participating in creation and implementation of program solutions for the regions’ development. This type of group is the subject of our article.

When considering expert groups, it is necessary to understand that they differ significantly in their nature and properties, namely, communicative, interactive, and perceptual processes, from the implementation groups of the first type [8]. Groups of the third type are a type of target groups, but they are created to perform the functions of monitoring (evaluating) the object of social transformation or forecasting its changes, planning the vectors of changes in the object. In the case of creating expert groups to form a strategy for the development of business organizations, sectors of the national economy or regions, the function of forming groups of the first type is added to the listed functions [9].

Expert groups consist of a specific number of participants; each of them has their own idea about the object of social transformation and pursues their own goal. Interaction can be carried out in the examination procedure, involving or not involving communication between the participants. Such a group also has a structure that reflects the role positions [9; 10].

The successful implementation of the expert group’s functions directly depends on the elements. This applies to achieving the effect of solidarity (consistency of opinions) [11] and correct cooperation arrangements [12; 13].

Thus, the members and quality of expert groups are the process result of expert group formation. The scientific explication of the definition of expert group formation in the branch sociological disciplines is currently absent, so we introduce three definitions that meet the purposes and tasks of our research: 1) general, social group formation as a spontaneous formation of population groups from interested citizens with pro-government and opposition attitudes for the implementation of national projects that have common and different interests in social transformations in their settlements areas; 2) real expert group formation is the actual distribution and members of experts in decision-making groups regarding the implementation of national projects and programs of management modernization in regions with different levels of socio-cultural modernization; 3) latent (potential) expert group formation is the potential for respondents’ participation as experts in decision – making groups, established through special sociological measurement procedures.

It is worth especially noting that the expert groups differ in their characteristics. In this regard, we should use the following parameters to identify them: people’s motivation to participate in groups, the presence of constant participants’ interactions, agreement (or disagreement) on the key issues [14; 15; 16]. They are the basis for determining the effect of expert group formation in our work.

Taking into account the selected parameters for studying the group formation processes, we rely on the interaction theory according to which people get to know each other in the process of frequent contacts. They form a sense of sympathy or antipathy, stable interaction forms and signs of collective subjectivity appear [13]. In addition, the authors use the provisions of the equilibrium theory according to which people with similar attitudes and values usually unite. Relationships become unstable if there is no balance there [13; 17; 18].

The article also takes into account the experience of applying expert assessments in the regional management practice. This refers to the organization of expert evaluation, experts’ selection (criteria), determining the type of experts’ interaction (offline or online, collective discussion or individual assessments), and methods of processing expert opinions for making a final decision [18; 19; 20].

Our research focuses on the importance of expert selection procedures. By now, there is no unified technology for selecting experts according to scientists’ opinion [14; 21].

Many researchers have noted the competence importance [22] or recommendations in the experts’ selection (expert group recruitment on the “snowball” principle) in the practice of managing organizations or technological forecasting. The scientists also often consider the level and profile of education, work experience in the subject area, job competencies for solving problems, personal qualities (mind flexibility, creative thinking, social activity, authority of the expert opinion), and the practice of working in expert groups (objectivity, independence, variability in assessments) [23].

However, in the regional management practice, these approaches need to be refined and reformatted. The diversity principle of expert positions and activation of stakeholders’ (subjects’) interest should be taken into account [24].

In our opinion, rather important is the assessment of value orientations and the experts’ attitude to the activities of regional authorities in the implementation of regional development programs. In this regard, the most appropriate ways to include a person in the expert group are not a posteriori and a priori methods of assessing an expert’s quality (participation or non-participation in past examinations), but test methods that determine an expert’s position in the system of key agents and their value orientations [25].

Testing and implementing experimental test approaches to identify the structures of real decision-making groups and latent (potential) experts is becoming the main task of our research and, undoubtedly, can improve the quality of regional governance and key strategic decisions.

Research design and methodology

The primary task of our research is to use the methodology of management sociology to test the possibilities of the sociological dimension of expert group formation as a management mechanism in regions with different levels of socio-cultural development.

There can be quite a lot of signs of group formation. It is often difficult to fix them, so we note the most important ones that can be determined by the expert survey method. First of all, we are talking about identifying the presence of experts’ interaction in solving a certain range of problems. As the context of our task is related to the solution of management problems of the region’s development, this parameter can be indirectly recorded by evaluating the experts’ participation in the activities of a particular project or program for the region’s modernization (state programs for the modernization of regional management systems and national projects). Their participation determines the activity vector or experts’ passivity.

The second parameter of group formation is the similarity of the views and the identity of expert opinions in the context of solving issues of socio-cultural modernization and regions’ strategic development. These grounds became the key for constructing the scale “supporting decisions” – “not supporting decisions”, representing data through the interpretation of expert assessments of the functioning and decisions of various parts of the power and management vertical, “support-non – support” of the general political and managerial course of the authorities and management. In fact, we define a progovernment group of experts (supporting) and the opposition (not supporting).

In the decision-making practice, the development of tools for establishing and fixing the combination of these two groups becomes a scientific and methodological task of our research.

To find a balance in the solution group, the authors use an approach borrowed from rationalizing social diagnostic technologies (A.V. Tikhonov, V.V. Shcherbina [26]). According to this approach, in order to form socially-oriented goals in management practice and overcome unforeseen consequences from management decisions, it is necessary to use special rational and cognitive procedures. They allow diagnosing the management nature (at different levels of society: societal, institutional, regional, managerialcorporate and local self-government) and designing the achievement of balanced decision groups with subsequent access to the creation of info-communicative feedback technologies.

As a result, the article carries out the experimental development of integral features of expert group formation which allow diagnosing and identifying not only real, but also latent (potential) groups of solutions. This point of view can either coincide with the authorities’ point of view or be oppositional.

Research progress

The research was conducted in 2019 in four pilot regions out of 12 ( Tab. 1 ) that N.I. Lapin have selected according to the rating of the regions’ socio-cultural modernization [27].

In general, the authors have collected and developed a database of 347 experts from four regions; 59.6% (207) of them took part in the survey and gave high-quality detailed answers to open questions.

The work has achieved the target of at least 50 experts from each region taking into account geographical affiliation, various activities, and status characteristics (managers, specialists).

Research results

Due to the fact that we chose two types of projects in which experts could participate, it was necessary to analyze the activity combination ( Tab. 2 ) . The experts’ participation in both projects indicates the group constancy and the interaction of its members, i.e. confirms the expert group formation according to the interaction theory.

Table 1. Entities of the Federation where the study is conducted

No. Region’s name Status of a Federal entity Federal District Level of socio-cultural modernization in points and text abbreviations (2016, according to the data of the CISI IF RAS) * Rating of the socio-economic situation of the regions of the Russian Federation, in points (2020, according to RIA-rating)** 1 Moscow Oblast Oblast Central 6 (H) 77.595 2 Republic of Bashkortostan Republic Privolzhsky 3 (A) 60.505 3 Belgorod Oblast Oblast Central (1) (BA) 57.103 4 Republic of Kalmykia Republic Southern (1) (L) 17.361 *    Integral indicators (in points) of the socio-cultural and socio-economic levels of the studied regions as a whole correlate in accordance with the presented rating data. * * Russian regions’ rating on the quality of life – 2020. Official website of the “RIA Rating Agency”. Available at: infografika/20200602/ (accessed: January 20, 2021). Level estimates of socio-cultural modernization are from the works of RAS Institute of Philosophy, led by Lapin N.I. (Source: Atlas Of Modernization Of Russia and Its Regions: Socio-Economic and Socio-Cultural Trends and Problems. Ed. by Lapin N.I. Moscow: Ves Mir, 2016, pp. 346–348), his co-authors or indicated by him personally; the points in parentheses are from the Map-Scheme of Modernization of Russia’s Regions (2010). Available at: (accessed: July 25, 2017). A.V. Tikhonov. A detailed description of the regions’ selection for the study is provided in: Russia: Reforming the Power and Management Vertical in the Context of the Problems of Socio-Cultural Modernization of the Regions: Monograph. Ed. by A.V. Tikhonov. Moscow: FNISC RAN, 2017, pp. 36–41. Acronyms: H – high, AA – above average, L – low, BA – below average, A – average.

Table 2. Experts’ participation in the implementation of national projects and programs of regional governance reform (aggregated data of expert assessments of four pilot regions), % of a number of experts

Participants in public administration reform programs	Do you participate in the implementation of national projects?
	2 г "° §. ® | ~ ■Ё с g- Ё — ® Е	О o'" ^ го ^	11 Е	S	Total
Already participate	6.3				6.3
Yes	12.1	15.5	1.4	1.0	30.0
Rather yes than no	9.2	18.4	6.3	3.9	37.7
Rather no than yes	1.4	2.9	6.8	1.4	12.6
No	0.5	0.5	3.9	1.0	5.8
Not sure	1.5	2.4	1.4	2.4	7.7
Total (207 experts)	30.9	39.6	19.8	9.7	100.0
Source: own calculations.

Only 6.3% of experts actively participate in these two programs (see tab. 2). In fact, this is an active and permanent core. However, 21.3% of experts can be added to this group; they are involved in the implementation of national projects and would like to participate in public administration reform programs. Their non-participation in the reform program is rather an evidence of the closeness of a group of decision-making subjects. In total, there are 27.6% of active experts, i.e. almost a third of the entire surveyed expert audience.

There is a fairly significant group of experts (33.9%), among whom there are those who are potentially set to participate in regional modernization programs, but, for reasons beyond their control, they were not included in the active groups. This also confirms the mechanism relevance for recruiting expert groups “from above”. There was also a group of experts who had information about the state of affairs in the region and the governance nature, but were not interested in participating in the decision groups. This is a passive part of the expert audience which makes up 10.7%.

There are those who found it difficult to answer: among them, 7.7% chose this answer in relation to the issue of improving regional governance and

• 9.7% – on the issue of participation in national projects. Difficulty in identifying the expert position on both projects was recorded only among 2.4% of experts. This group can be activated under certain circumstances to participate in the region’s management.

As a result, out of the entire expert group, the share of active experts is 30.9%, potentially active – 52.2%, and passive – 14.5%. The data indicate the existence of expert group formation in the civil management of regional development and also indicate a great potential, i.e. the presence of latent expert group formation in the regions.

Next, we consider the second feature of expert group formation – “supporting solutions” and “not supporting solutions”. The authors calculate it as the attitude to the authorities’ activities, namely, through the assessment of satisfaction and trust in the authorities in the management of the region and the country as a whole. This parameter allows determining the nature of existing groups, the consistency of their value orientations which are important in making managerial decisions. We have fixed this attitude by determining the position of experts regarding the activities of various authorities and management bodies.

To determine the assessments’ structure, we have initially carried out a correlation analysis of the assessments of the authorities’ activities using the Kendal coefficient, as the assessments were an ordinal five-point scale. The analysis proved that all estimates significantly correlate with each other at the significance level of p < 0.01. However, not all correlations presented a noticeable relationship. The authors have selected those relationships that had a correlation coefficient greater than 0.51. As a result, it was possible to build a pleiad that reflects the structure of the relationships of assessments.

The scores are clearly divided into two groups. The first includes assessments of federal authorities, the second – regional ones. The similarity of expert assessments of the authorities and management indicates a certain and potentially possible integration both within regional authorities and within federal structures. At the same time, the activities of the federal authorities differ from the activities of the regional ones, i.e. a certain gap in the work of the power’s vertical is fixed. It is quite interesting that the second group also includes assessments of the activities of the internal affairs bodies (police). Apparently, experts evaluate their activities based on regional experience. The estimates of the enterprise administration were weakly correlated with other ones, as the parameter had a small variation. The assessments of the judicial system and the regional media were quite interesting. These parameters are the link that connects two selected groups. The judicial system is evaluated from the top down, so it reflects the activities of the federal and regional levels. As for the regional media, on the one hand, they focus on the practice of the central media and, on the other, show the city government’s interests. This fact lets assuming that the regional media’s activities are more dependent on local authorities which, in turn, exclude the possibility of broadcasting diverse points of view there about solving certain problems in the region.

The expert opinions’ analysis made it possible to integrate the estimates of the studied parameters in each group and to aggregate the estimates of the work of federal and regional authorities on the basis of arithmetic averages. Due to the fact that the parameters “enterprise administration”, “judicial system”, and “regional media” were closely related to both groups, they were excluded from the indices which ultimately helped to achieve a higher purity of the estimates of the two main groups.

Further, we have converted the evaluation indices into a nominal scale by gradation (negative and positive ratings) and created their combination. As a result, we got four expert groups. The first one consisted of experts who were satisfied with the work of all authorities. The second group is satisfied with the federal authorities’ work and is not satisfied with the activities of the regional ones. The third group is satisfied with the activities of the regional authorities and is dissatisfied with the federal authorities. The fourth group of experts is dissatisfied with the activities of all authorities. A fifth group was also created. It included experts who found it difficult to assess the activities of the authorities and management.

Tables 3–6 provide an opportunity to assess the balance of the distribution of expert group formation in the implementation of strategic decisions of national project taking into account the experts’ commitment (approval) to the course of federal and regional management.

Next, it is worth considering the group structure of decision-making entities. It will show what the success of managing the region depends on.

It turned out that the share of active experts in the Moscow Oblast is 27.4%, Bashkortostan – 26.0%, Belgorod Oblast – 33.3%, Kalmykia – 40.0%. First of all, these data indicate that there is a real expert group formation in the regions. Probably, important stakeholders are included in the practice of managing subjects. However, in more developed regions, the percentage of active experts is lower, i.e. people get into the expert group after a certain selection. As for the latent group formation, its effects are present in all regions. In the Moscow Oblast, the share of those who want to take part in the management of the region is 52.9%, Bashkortostan – 46.0%, Belgorod Oblast – 64.7%, Kalmykia – 50.0%. The peripheral nature and alienation of this latent group of experts from management may be a consequence of the prevalence of the “authoritarian-clan” management style in the regions and the focus on reporting to higher authorities which was established in our previous study (RSF project 2015–2017).

The percentage of experts, involved in the development and decision-making on a permanent basis (the core of the group), is quite small: 9.8% in the Moscow Oblast, 6% in Bashkortostan, 7.8% in the Belgorod Oblast, and 2% in Kalmykia. Low percentages indicate a constant restructuring of the expert group to solve certain types of problems which is adequate in management practice

(G. Simon). However, in the Moscow Oblast, as a region with a high level of socio-cultural modernization, the percentage of the core is slightly higher compared to other subjects.

The presence of latent groups, which are experts with different value orientations, allows managing the solution group and restructure it depending on the tasks. This possibility exists in all regions, as the ratio of pro-government and opposition experts are approximately equal. But it is worth noting that, in Bashkortostan, the share of potentially active and oppositional experts (who criticize all authorities) among the entire expert body is quite small (6%).

In our opinion, in the decision groups (experts involved in the implementation of modernization programs), it is necessary to achieve a balance in the distribution of expert groups that have different attitudes and assessments about the activities of government and management bodies. This will allow achieving a balanced and constructive nature of strategic decision making at the regional level.

Table 3. Groups of experts included / not included in the decision groups, in accordance with their assessments for federal, regional, and municipal authorities (aggregated data of experts from the Moscow Oblast, 2019), %

Groups included/not included in the decision groups	Ф ф Е ф та 5 ф =	Е Е CD ^ СО S Ф ОО О Ф Е М та СО CD гага С ^ ^ ф	г 11 ° CD о Е о га || о ф 05 Ф ф > ф О 1 °	1 ста та 5	та ZE		1		о
Distribution across the entire data set
In the solution core	3.9			3.9	2.0	9.8	13.7	4.0	9.8	27.4
Active expert group	9.8		5.9		2.0	17.6
Interested, but not participating	23.5	3.9	9.8	15.7		52.9	23.5	0.0	29.4	52.9
Passive expert audience	5.9	2.0	3.9	5.9	2.0	19.6	5.9	2.0	11.8	19.6
Total	43.1	5.9	19.6	25.5	5.9	100.0	43.1	5.9	51.0	100.0
Distribution in the group of active experts
Core	40.0			40.0	20.0	100.0	50.0	14.3	35.7	100.0
Active expert group	55.6		33.3		11.1	100.0
Interested, but not participating	44.0	7.4	18.5	29.6		100.0	44.4		55.6	100.0
Source: own calculations.

As a result, we can expect real social effects with the least negative consequences. Due to the fact that the Moscow Oblast is a more developed territory, it accounts for the most optimal distribution of expert groups ( Tab. 3 ) .

The decision core includes not only those experts who fully share the planned course of the authorities and their current activities on all levels of the power and management vertical (3.9%), but also an expert group that gives negative assessments to all authorities and systematically criticizes their functioning (3.9%; see Tab. 3).

As a result, the ratio of experts in the core is 40:20:40, i.e. there is a balance of pro-government and opposition groups, while 20% are undecided experts who, when making a decision, tend to side with those whose arguments are more significant.

However, if we consider the entire active group of experts, the proportion changes (50:14:36). Apparently, when making decisions, there is a problem of lack of consensus. To eliminate it, experts are recruited in such a way that half of them support the programs proposed by the authorities. A third is the opposition which can attract waverers to its side and, in this way, change the course of the vote. This opposition is represented to a greater extent by experts who share the course of the regional authorities, and to a lesser extent by “pure” oppositionists (who criticize all levels of government). There is a situation when a number of pro-government experts begins to prevail, the probability of making decisions in favor of the government increases, but the opinion of the opposition, which shares regional interests, is taken into account. A small “pure” opposition acts as a group that conveys alternative (inconvenient for the authorities) information, but its opinion is also taken into account when making a decision.

The Moscow Oblast has latent expert groups representing different points of view on the practice of regional management. They form the basis for managing the solution group (the re-structuring).

We should note that this is not an ideal picture, but rather the most satisfactory one compared to other regions, related to the balance of expert group formation in decision groups.

In the Republic of Bashkortostan, which is at a lower level of socio-cultural development, the picture is slightly different ( Tab. 4 ) .

The core group includes a group that positively assesses the authorities’ activities (2%). However, there are also two other groups, the first of which positively assesses only the work of regional authorities (2%), the second one negatively assesses the activities of all authorities (2%). The result is a combination of experts 33:0:67. There is a clear opposition group. It can act in its own interests, and their vector is not always aimed at humanization. However, the percentage of the core is small, and, when considering the entire active group, the ratio will be approximately 70:7:23. We see that the group is selected in such a way that the majority are pro-government experts. Then there is a large group of oppositionists who share the policy of the regional authorities, and a smaller group of “pure” oppositionists. However, in Bashkortostan, the share of pro-government experts is much higher than in the Moscow Oblast. In the region, in our opinion, there is a deliberate “squeezing” of the opposition from the decision group. There is no possibility of correcting the balance, as the number of “pure” oppositionists in the latent groups is relatively small (6%), and there is no potential for recruiting oppositionists from among passive experts.

In the Belgorod Oblast, only pro-government experts represent the core (7.8%; Tab. 5 ). If we consider the entire active group of experts, the ratio will be 88:0:12. Here, the bias toward progovernment opinion is obvious, and the experts’ selection does not change the situation in the core. The detected bias can be corrected by latent groups, as the potential for expert group formation is quite large.

Table 4. Groups of experts included / not included in the decision groups, in accordance with their assessments for federal, regional, and municipal authorities (aggregated data of experts of the Republic of Bashkortostan, 2019), %

Groups included/not included in the decision groups	CD ф E ф СУ 5 > =	2 E CD 00 CD U) <П CD E В CO CD Ш S ^ Ф ф	2 | | ° ® о 1 55 CO CD _ ||| CQ СУ CD Z > О	1 VD E ф 2	СУ ZE		1		о
Distribution across the entire data set
In the solution core	2.0		2.0	2.0		6.0	18.0	2.0	6.0	26.0
Active expert group	16.0		2.0		2.0	20.0
Interested, but not participating	24.0	2.0	2.0	6.0	12.0	46.0	24.0	12.0	10.0	46.0
Passive expert audience	26.0	2.0				28.0	26.0	0.0	2.0	28.0
Total	68.0	4.0	6.0	8.0	14.0	100.0	68.0	14.0	18.0	100.0
Distribution in the group of active experts
Core	33.3		33.3	33.3		100.0	69.2	7.7	23.1	100.0
Active expert group	80.0		10.0		10.0	100.0
Interested, but not participating	52.2	4.3	4.3	13.0	26.1	100.0	52.2	26.1	21.7	100.0
Source: own calculations.

Table 5. Groups of experts included / not included in the decision groups, in accordance with their assessments for federal, regional, and municipal authorities (aggregated data of experts of the Belgorod Region, 2019), %

Groups included/not included in the decision groups	су Е 5 >	® о о Ъ 1 ” с с ” о й о ° 5	05    Ф -^ Ф о О ф ш ф Ф О	1 Е ф СУ 5	су ZE		1		о
Distribution across the entire data set
In the solution core	7.8					7.8	29.4	0.0	4.0	33.3
Active expert group	21.6	2.0	2.0			25.5
Interested, but not participating	33.3	2.0	15.7	11.8	2.0	64.7	33.3	2.0	29.5	64.7
Passive expert audience			2.0			2.0	0.0	0.0	2.0	2.0
Total	62.7	3.9	19.6	11.8	2.0	100.0	62.7	2.0	35.3	100.0
Distribution in the group of active experts
Core	100.0					100.0	88.2		11.8	100.0
Active expert group	84.6	7.7	7.7			100.0
Interested, but not participating	51.5	3.0	24.2	18.2	3	100.0	51.5	3	45.5	100.0
Source: own calculations.

The Belgorod Oblast occupies a special position, as the Center for the Sociology of Management and Social Technologies of the ISRAS has identified a fairly well-organized management system that achieves the planned strategic goals at the regional level (according to experts) regardless of a low level of socio-cultural development according to the RAS Institute of Philosophy. There is also an active audience of independent social actors (agents) who are ready to participate in the development and implementation of management decisions at the level of their municipalities and the region as a whole. This fact is confirmed by the data of our research: the share of potentially active experts is 64.7%. The identified latent group is mixed. The opposition is represented by 15.7%. These experts give positive assessments to regional authorities and negative assessments to federal authorities, as well as 11.8% of absolutely oppositional experts. The last group is not allowed managing. Perhaps, if this were not the case, the region would be higher in the rating of socio-cultural modernization.

In the Republic of Kalmykia, the core consists of only 2% of experts, i.e., in the region, in fact, real expert groups are not represented ( Tab. 6 ) . The groups are modified each time, and in such a way that the total share of experts making decisions is greater than in the rest of the regions as a whole, it is 40%.

We can assume that “extra” experts are invited to the groups for solving certain issues in Kalmykia, who can change the decision in an unconstructive way. They are selected in approximately the same way as in the Moscow Oblast. Their ratio is 55:0:45. We can note a small preponderance of progovernment experts and a fairly large opposition group. A potentially balanced group is not traceable. At the same time, we note that there is only 10% of “pure” oppositionists in the opposition group. Unlike the Moscow Oblast, where there is a fairly large group of opposition experts who share the policies of the regional authorities, there is no such group in the studied region. It has been replaced by a group that supports the federal authorities, i.e.

Table 6. Groups of experts included / not included in the decision groups, in accordance with their assessments for federal, regional, and municipal authorities (aggregated data of experts of the Republic of Kalmykia, 2019), %

Groups included/not included in the decision groups	03 E ф ro 5 >	8 В ™ c c ” CD ТЗ О ГО ^ ^ ^ ” О § s ^ 1	О ш ” Ф ГО о	1 VD E ф ro 5	ro ZE		1		о
Distribution across the entire data set
In the solution core	2.0					2.0	22.0	0.0	18.0	40.0
Active expert group	20.0	8.0		10.0		38.0
Interested, but not participating	20.0	10.0		12.0	8.0	50.0	20.0	8.0	22.0	50.0
Passive expert audience	4.0			2.0	4.0	10.0	4.0	4.0	2.0	10.0
Total	46.0	18.0		24.0	12.0	100.0	46.0	12.0	42.0	100.0
Distribution in the group of active experts
Core	100.0					100.0	55.0		45.0	100.0
Active expert group	52.6	21.1		26.3		100.0
Interested, but not participating	40.0	20.0		24.0	16.0	100.0	40.0	16.0	44.0	100.0
Source: own calculations.

the opinion is shifted toward supporting the federal authorities. When addressing issues of regional development, there is an imitation of considering different points of view. The region’s needs are represented to a small extent. There is a potential for recruiting opposition members from among the latent groups in the region.

As a result, based on a general analysis of the data, we naturally record that in regions with higher socio-cultural development (Moscow Oblast), the decision-making group on management issues contains a fairly large proportion of opposition experts which allow looking at the problem situation from a different angle. Opposition groups provide more relevant information and more often represent the interests of the active part of the population in decision-making. Less developed regions create expert groups in such a way that they are dominated by pro-government experts who support the point of view of the authorities, and they will broadcast it to the masses. In the Moscow Oblast, the ratio of pro-government and opposition experts was 50% and 50%, in Bashkortostan – 69% and 23%, in the Vologda oblast – 88% and 11%, respectively. However, this pattern is violated by the experts of the Republic of Kalmykia. Here, the ratio of progovernment and opposition experts turned out to be 55% to 45%, so the revealed pattern will need to be confirmed on a larger array of data from other entities of the Federation.

Currently, the successful combination of decision-making groups is 3:2:1 (pro-government, supporting regional authorities, “pure” oppositionists). This combination: a) allows the regions not to go against the federal policy and maintain the internal integration of the country at the same time; b) to take into account and, if possible, defend the region’s interests; c) to receive unexpected information from absolutely opposition groups. The opposition can produce irrational (dangerous) decisions that run counter to the course of progovernment strategies, so the share of “purely”

opposition-minded experts in the decision group is always lower than in other groups. Focusing on the expert ratio in the Moscow Oblast, it is worth considering another distribution – 2:1 (confident in their position, fluctuating; see tab. 3), so that a positive opinion can be formed in the floaters’ group at the expense of more evidential arguments of the pro-government or opposition groups.

Latent groups of active experts represent different positions and attitudes. Their presence indicates the possibility of managing expert group formation. In addition, the regions do not practice the use of a single biased group (only the core) of experts to solve all issues. Management potential (the presence of latent expert groups with different value orientations) is possessed by all the entities considered, with the exception of Bashkortostan, where the latent group is large, but the share of the opposition is small.

As for the entire expert group as a whole, it is less active in developed regions than in undeveloped ones. The share of passive experts in the Moscow Oblast and Bashkortostan is 19.6% and 28%, respectively, and in Belgorod and Kalmykia – 2% and 10%. This can be interpreted as follows: in more developed regions, an institutional management system has already been formed. It does not require manual management including the invitation of a large number of experts. Development and management go their own way; so many experts are busy with professional responsibilities and do not see the point of participating in the expert groups of the solution.

Conclusion

Based on the explication of expert assessment, we have managed to establish the nature and state of real and latent expert group formation in four pilot regions with different levels of socio-cultural modernization. In particular, the authors consider the sociological features of expert group formation in the context of “activity vs passivity”, “supporting decisions” and “non-supporting decisions”.

The data analysis shows that the established nature of export group formation depends on the degree of the regions’ socio-cultural development. More developed regions have more diverse decision groups with experts having the largest range of opinions and attitudes. The inclusion of opposition experts in the main group allows achieving the most constructive solutions in the practice of implementing national projects and programs for the regions’ modernization. However, this pattern manifested itself only in three out of four regions; to confirm it, data on a larger number of entities are required.

We also have recorded that there really is a large active group of experts involved in the practice of making managerial decisions in the four pilot regions. It is modified depending on the nature of the solutions being developed at the level of a specific area. As for the decision group, its core more often includes the experts whose opinions and attitudes reflect and support the strategic course of federal, regional, and municipal authorities (except Moscow Oblast).

The research assumes that the authors will collect the necessary data in the course of further study to confirm the correctness of the selected balance of expert assessments and groupings. In addition, in the future, we are planning to consider the coherence of expert assessments of the government’s activities and management bodies, as well as assessments of political decisions that allow determining the essence of discontent or support. This data may need to adjust the attributes of the selected group balance.

In the management practice, the system of balance assessments of decision groups can become the basis for studying the candidates’ potential for expert groups. In our opinion, this is an important practical management and research task of the branch scientific discipline of the management sociology.