EXPLAINING ECONOMIC AND SOCIAL TRANSFORMATIONS IN POST-SOVIET RUSSIA, UKRAINE AND BELARUS: The social quality approach

The collapse of communism in the USSR in 1991 resulted in rapid and dislocating economic and social changes, which have been little short of cataclysmic (e.g., Burawoy 1997, 2001; Sztompka 2002; Abbott and Wallace 2009; Shevchenko 2009). The economic transition from planned market economies was accompanied by economic crisis exemplified in declining GDP, hyperinflation and cuts in state welfare spending. The social impact of transition can be seen in the increase in inequalities, rising poverty, unemployment, and violent crime, a decline in trust, a decline in well-being and de-modernisation with the majority of the population being ‘losers’ (Abbott and Sapsford 2006; Pridemore et al. 2007; Abbott and Wallace 2009; Rose 2009).

In this paper we explore the relationship between the economic and the social impact of the transformation, seldom analyzed as most analysis has drawn upon liberal economics, more recently modified by the neo-institutionalist school of economics (Pickles and Smith 1998). In these explanations, the situation of individuals is ‘determined’ by external and inevitable economic forces: individuals’ perceptions are considered irrelevant or at best as offering colourful illustration. However, we argue that in order to understand how economic transformations at a national level lead to specific problems, such as a decline in health, at the micro level of the individual we need to take into account the role of agency, meaning the scope for individuals to act within the context of structural changes. This requires an analysis of the impact of the transition on the agency and biography of individuals and the coping strategies adopted as they survive in the face of disruption and uncertainty. Relating objective welfare conditions to subjective perceptions of well-being (Fehey and Smyth 2004) opens the space for understanding peoples’ responses to structural change and the impact it has on their ability to take control over their lives and developing their capabilities (Sen 1993). A useful heuristic framework for such an analysis is provided by the Social Quality approach (see e.g., van der Maesen and Keizer 2002) which measures the quality of the social context of everyday life, providing a sociologically grounded theoretical concept that defines the space within ‘which citizens are able to participate in the social and economic life of their communities under conditions, which enhance their well being and individual potential’ (Beck et al.2001: 25).

The approach focuses on the individual, as an active subject living in developing social conditions. The ‘Social’ is seen as the outcome of the dialectical relationship between the formation of collective identities and the self-realisation of the human subject, between global processes and biographical processes on the one hand and between system integration and social integration on the other. The ‘social space’ is realised in and between four constitutive factors:

• •

  economic security, having available the necessary material resources;

• •

  social cohesion, the necessary collectively accepted values and norms are in place;

• •

  social inclusion, having access to the necessary institutional and infrastructural context; and

• •

  the conditions for empowerment enabling people to have control over their own lives and the capacity to act

It is possible to use the model to elicit a number of key indicators that can be used for empirical analysis to evaluate the quality of a society – indicators that are both objective and subjective. Ultimately, however, we need to understand what the main influences on subjective life satisfaction are, as it is subjective experience that influences agency and peoples’ ability to take control over their lives (Land et al. 2007; Richardson et al. 2008). The ultimate concern is with the specification of a liveable society for all (Herrmann and van der Maesen 2008).

In this paper we examine the social impact of the transition using the Social Quality model as a framework. We take subjective life satisfaction as being the final outcome of Social Quality and we end with a multiple regression that measures the relative impact of the four quadrants on life satisfaction.

Our analysis is based on survey and qualitative case study data for Belarus, Russia and Ukraine collected as part of the Living Conditions, Lifestyles and Health Project, a multi-level study of the impact of the transformation on health and well-being.

The cross-sectional survey was carried out in 2001 using face-to-face interviews with a representative sample of the adult population. The questionnaire for the survey was developed by the project partners translated into Russian piloted, modified and back translated into English for final checking. Multi-stage sampling with stratification by region and area, and gender and age was used with a sample size of 2,000 in Belarus (as this provides reliable estimates of proportions that represent 3 percent or more of the population at the national level with a precision of 0.75 percent for most countries) but a larger number in Russia (4,000) and Ukraine (2,400) because of their significantly larger and more diverse populations The response rates were 76 percent in Ukraine and 73 percent in Russia and Belarus. There was a 10 percent call-back for quality control. The data was input into the Statistical Package for the Social Sciences for analysis.

Seven qualitative case studies, comprising in total of 290 interviews, 38 expert interviews and 18 focus groups, were carried out in 2002/2003, one in a more affluent area and one in a more deprived area in each of Russia (Archangelsk and Samara) and Ukraine (Kherson and Lviv), and one in each of Russia, Belarus and Ukraine in the Chernobyl Region (see Table 1 for the purposeful sampling framework). (Chernobyl was included in the research as a case study because we were interested in the impact of the nuclear accident on health and well-being. See Abbott et al. [2006] for an analysis of the findings for this region.)

The research assistants were locally employed sociologists trained by us in qualitative interviewing and data analysis. The agendas for the interviews and the topics for the focus groups were developed with them and we maintained contact during the fieldwork phase and made field visits. Interviews and focus groups (in Russian, except in Western Ukraine where Ukrainian was used) were recorded and transcribed and we worked with the research assistants on a sample of translated interviews to agree the main themes and construct an index using the Framework system (Ritchie and Spencer 1993). The research assistants then constructed the matrix charts for the individual interviews and a research assistant translated them into English. The focus groups and expert interviews were translated into English and we analysed them.

To determine the influences on life satisfaction a series of linear regressions using indicators derived from the social quality model controlling for age and gender were carried out using the entre method with the dependent variable being a seven point index (the Life Satisfaction Index) computed from the happiness and general satisfaction variables (see Appendix 1). The means and standard deviations for the scale (Belarus M 4.37, SD 1.47; Russia, M 4.39, SD 1.46; Ukraine M 3.89, SD 1.52) suggest that subjective well-being is relatively poor with the Ukrainians reporting the poorest. (Conversion to Z scores indicated that the range is relatively small, from −2.2SDs to+1.8SDs, and the distribution roughly normal, with just over 60 percent of the population in Belarus and Russia lying within ±1SD slightly skewed to the positive, but in Ukraine the distribution was negatively skewed with nearly 40 percent of the population being more than –1SD from the mean and less than 10 percent more than +1SD.)

Finally we computed the Index of Social Quality from the variables that were significant at the 99.9 percent level in the final model. We normalised the indicators (converted them to Z scores), added them together and then renormalized. This enables us to consider the distribution of Social Quality in the three countries

The strength of multivariate modelling is that it enables us to detect underlying patterns and evaluates the main influences on the index of life-satisfaction. Nine of the independent variables were scales computed to summarise a number of related questions (Appendix 1 and Table 7 below). We constructed the scales using factor analysis with varimax rotation and all have acceptably high Cronbach alpha values. We used scales because one question is not sufficient to measure a multi-dimensional construct and using composite scales reduces random variation in responses to individual questions so that what is lost in detail is gained in stability. The model was tested for multicollinearity and found to be satisfactory, the tolerance of no variable being below 0.40.

Next we turn to the dimensions of transition in terms of the different aspects of Social Quality using data from both the survey and the qualitative case studies. This enables us to provide a much richer understanding of the liveability of post-Soviet societies than previous work that has been based on an analysis of the survey data alone (Abbott and Sapsford 2006; Abbott 2007; Abbott and Wallace 2009). (For clarity we refer to those who participated in the qualitative case studies as informants and those who took part in the survey as respondents.)

Economic security became more precarious in the 1990s. Real GDP declined (although it had recovered somewhat by 2001 it remained below 1989 levels), unemployment increased and the real value of wages declined. Hyper inflation made savings and benefits virtually worthless.

Over three-quarters of the survey respondents thought that the disintegration of the Soviet Union had had a negative impact on the economy of their country and nearly half thought that their own economic situation had got worse. Only around a fifth of respondents (21.7, 23.6 and 19.0 percent, respectively, in Belarus, Russia and Ukraine) thought that their economic situation had improved. While about two-thirds rated the state of the economy at the time of the Soviet Union highly, only a very small minority similarly rated the present state of the economy highly, 15.9 percent in Belarus, 10.7 percent in Russia and 3.1 percent in Ukraine. In the qualitative case studies informants expressed general dissatisfaction with life and many said they were struggling to survive (Table 2).

Our informants kept returning to their financial difficulties and lack of financial security. They reported having to work much harder, often having more than one job, growing their own food and not being able to relax in the evenings or at weekends. For the majority making ends meet was hard work with little rest, a break from work or a holiday.

One way people survived is by informal economic activity to supplement or replace income from the formal economy (Abbott and Wallace 2009). A majority of informants had a plot of land, the produce from which was a major source of food, enabling them to control economic uncertainty. ‘Good diet is impossible without a supplementary plot of land’ (Male, Russia). In Chernobyl many people had returned to the area despite the radiation in order to get employment; as one informant put it: ‘It is better to die of radiation than of hunger. I don't care if it is dangerous working in the 30 kilometre zone (i.e., the forbidden zone). What is important is that I have a job’ (Male, Chernobyl region). The inability to afford to go on holiday any more was also frequently mentioned:

There has also been a real decline in the social wage – state and employment-related non-monetary benefits. There has been a loss of taken for granted services and facilities. Informants felt that the implicit social contract between them and their employers and state had been broken. ‘Pensioners worked all their lives and now they don't have anything’ (Female focus group, Ukraine). A male Russian informant suggested that: ‘If you don't care for yourself, the state doesn't provide for you. The state doesn't support people … you have to take care of yourself’.

Respondents to the survey were also generally dissatisfied with their own and their households income, varying from just over 70 percent in Belarus to over 85 percent in Ukraine. Over three-quarters said that their income was either insufficient, or only just sufficient, to buy basic food and clothes, varying from 78.3 percent in Belarus to 87.9 percent in Ukraine. A significant proportion of respondents said that they sometimes or always had to do without basic food – 36.6, 47.5 and 66.6 percent, respectively, in Belarus, Russia and Ukraine – while some could not always afford heating – 17 percent in Belarus, 21.2 in Russia and 68.3 in Ukraine. Conversely less than a quarter said they could afford to buy major goods such as a television. In terms of material circumstances we were able to identify four groups: the affluent, less than 2 percent of respondents; the financially secure, about a tenth of Ukrainians and a fifth of Russians and Belarusians who were able to enjoy a decent standard of living (securer); the poor, accounting for around two-thirds of Russians and Belarusians and nearly 60 percent of Ukrainians; and the improvised, about a tenth of Russians and Belarusians and nearly 30 percent of Ukrainians (Table 3).

Few of our informants said that they were well-off, and those that did did not report affluent lifestyles, more that they had an acceptable/decent standard of living:

The poor, by far the largest group, got by, by combining income from more than one source and often growing food on a plot. A male schoolteacher in Belarus who also did private tutoring said:

The improvised struggled to survive. Some informants were able to provide adequately for their children but did without themselves; others were able to feed their family adequately during the summer when they had produce from their plot to supplement the diet but not at other times of the year. Others struggled all the time to get by

The difficult financial circumstances for many means that they are excluded from engaging in activities they had previously taken for granted. Some were concerned that they could not afford to pay for the private tuition necessary to get their children into university. Many said they could not afford to pay for adequate health care:

Social cohesion refers to the extent that a society is integrated. One measure of social cohesion is the level of material inequalities in a society (Wilkinson 1996). Social inequalities, as measured by the Gini coefficient have increased, with the most significant growth being in Russia and Ukraine (Table 4). Levels of trust and fear of crime are also good indicators of social cohesion (Phillips 2006). A majority of survey respondents and qualitative case study informants said that their material circumstances had got worse but there was some awareness that there were some winners as well as losers. The members of one of the female focus groups in Ukraine suggested: ‘In the past the stratification of society was less’

The responses to the survey questions on trust and fear of crime suggest societies with low levels of trust and high fear of crime (Table 4) with over half the survey respondents fearing crime in their home and on the streets. The informants in the qualitative case studies also concerned about increasing crime.

Levels of general trust and trust in government and political institutions are relatively low (Sapsford and Abbott 2006) with the least trusted organisations being in political parties, with less than a quarter of Belarusians, about a sixth of Russians and just over 10 percent of Ukrainians trusting them. There were also relatively low levels of trust in the mass media. For example, an informant in Belarus, a female newspaper employee, told us: ‘There are less and less subscriptions to the newspaper. They don't trust us and they read the paper less’. There was a loss of faith in government and some nostalgia for the old regime which was seen as having been able to ensure social cohesion and economic security. Few of the respondents to the survey rated their present government highly (24.3 percent in Belarus, 17.2 percent in Russia, 3.9 percent in Ukraine), whilst over 50 percent rated the government in the USSR highly. One male focus group clearly blamed the government for the present situation – which they evaluated negatively – ‘It is the state that has led us to this’ (Male focus group, Belarus), and others clearly thought that things would be better if there was a return to communism – ‘I liked the regime that was. We lived communism’ (Male informant, Russia). Others, however, wanted to move forward. ‘My dreams and plans are to have a new government in our country, for people to be able to live in a normal way, then productivity will rise and the economic situation will improve’ (Male informant, Chernobyl). Few informants were satisfied with the rate and direction of change. There was a general view that the state was not taking care of its citizens.

Social inclusion relates to the integration of individuals into society. The three countries have high levels of integration at the micro level but there is a lack of social integration into the wider society, with some evidence that social exclusion has increased since 1991 (Rose 2009): ‘The main thing is that everyone gets along with each other (and) it was better when everyone had the same’ (Ukrainian focus group). A majority of respondents voted in elections but less than three-quarters of Belarusians, just two-thirds of Russians and only just over a half of Ukrainians expressed pride in their citizenship (Table 5). Active membership of clubs or other organisations was low – well under 10 percent – and few regularly participated in religious worship. Lack of time, social tension and financial factors seemed to be the main reasons for a decline in participation. A Belarussian informant indicated: ‘In the past people gathered in the club, the club was heated, now it is cold in the club, there is no place to go’. A number of informants pointed out that bathhouses had been closed down because there was no money to maintain them and the medical experts said that most people did not join sports clubs because they cannot afford the fees.

In sharp contrast, at the micro level the vast majority of our respondents had good social support and strong ties with friends and relatives. Over 90 percent of the survey respondents said that they had someone they could share their private feelings and concerns with and around 90 percent said they had someone they could rely on in a crisis. Just over 70 percent said that they never felt lonely, and a similar proportion said there was someone who would lend them money in an emergency (Table 5). In the qualitative case studies frequent mention was made of the responsibility of supporting and helping members of the family, of visiting the family and being able to rely on the family in times of need. Friends were also seen as a source of support.

However a small number of people were isolated and did not have family or friends:

Empowerment is the extent to which people are equipped to be and feel in control of their lives. The overwhelming impression from our informants was of a sense of resignation and hopelessness.

Others indicated that they could not take control over their lives because of a lack of financial resources:

One of the medical experts suggested that lack of control was a major reason for the poor health status of the population:

Few of the survey respondents thought they had any ability to influence political decisions, only just over a third thought they were free to engage in political activities, over 50 percent were afraid of illegal arrest and only around half thought they had freedom of choice and control (42.7 percent Ukraine, 49.9 percent Russia, 56.9 percent Belarus), although over three-quarters thought they had freedom of speech, freedom to join organisations, freedom of religion and were free to travel (Table 6).

Health or lack of it is an indicator of empowerment impacting on the ability to take control over life and to participate in normal day-to-day activities. The levels of poor health reported in our survey were very high, especially for women, with around a third of men and a half of women reporting less than good health. (Controlling for age women are significantly more likely to report poor health, chi-square P<0.001.)

Psychosocial health is also a key indicator of not feeling in control of one's life. In our survey we asked 14 questions that factor into two scales: one measuring malaise and one person control (see Appendix 1). Over 50 percent of respondents reported feeling that life is too complicated and a similar proportion reported that they get spells of exhaustion/fatigue. Over 40 percent reported not enjoying their day-to-day activities, feeling under constant strain and having insomnia. Less than 20 percent of men and 10 percent of women reported having no symptoms while over half the respondents report having five or more symptoms, and around a fifth having 10 or more. Women are both significantly more likely to report each of the individual symptoms and to have more symptoms on average than men (chi-square P<0.001).

Social Quality is distinct from both life satisfaction, citizen's subjective assessment of their social experiences, and quality of society based on objective socio-economic indicators, being based on the articulation of objective and subjective indicators. It provides the space within which social actors can exercise agency; high Social Quality enables individuals to exercise agency to achieve self-realisation in a social context. A decline in Social Quality will be associated with a reduced ability of citizens to exercise agency. We have argued in this paper that there is clear objective and subjective evidence that there has been a decline in Social Quality, post-1991, and that all three societies have poor Social Quality, with Belarus having the highest and Ukraine the lowest. One objective indicator of the negative impact of the decline in Social Quality is the dramatic decline in life expectancy for men in mid-life and the increase in poor health, especially of women (Wallace and Abbott 2009). Subjective indicators of the impact of the decline in Social Quality are a reduction in self-reported general satisfaction and happiness (Veenhoven 2001; Abbott and Sapsford 2006). We computed an index combining the answers to the questions on subjective satisfaction and happiness to form an Index of Subjective Quality of Life.

First we ran regressions, using the entire method for each of the quadrants separately and also tested the variance explained by age and gender to determine which indicators to put in our final model (Tables 7 and 8). Age and gender both made a small but significant contribution to variance explained (5.4 percent) with the younger people and men having a higher subjective quality of life. The variables selected to be indicators of economic security, measuring both relative and absolute poverty, explained 25 percent of the variance, all making a significant contribution, showing, not surprisingly, that the poor are less satisfied than the better off. Those selected to measure social cohesion, trust variables, fear of crime and satisfaction with political developments, explained 10.8 percent of variance with trust in other people, trust in government and fear of crime all making a significant contribution. The indicators selected to measure social integration explained 13.7 percent of the variance with all except regularly worshipping making a significant contribution, and those that were integrated being more satisfied than those who were not. The variables selected to measure feelings of empowerment and control and the ability to exercise agency explained 29.5 percent of the variance, with all making a significant contribution and with those reporting good physical and mental health and being able to control and influence their lives being more satisfied.

Next we took all the variables that were significant and entered them together, controlling for age, gender and country. The total model explained 43 percent of the variance with neither age nor gender making a significant contribution. (There is some indication that the Belarusians experience a lower quality of life and the Ukrainians a higher one than would be predicted by our model, but the Betas are very low and the difference only significant at the 95 percent level.) We ran a model for each country and confirmed that it held for each with only minor differences (see Table 8).

It is clear that economic circumstances and empowerment indicators make the largest contribution with self-reported health making the largest contribution, followed by the economic circumstances of the family and control over ones life. Having an adequate income, being physically and mentally healthy and feeling in control are clearly the most important predictors of subjective well-being. However, trusting other people, pride in citizenship, personal support and close ties are also important.

We computed an Index of Social Quality from the variables that were significant at the 99.9 level. The minimum value on the index was −4.2 and the maximum value +2.7 with 60 percent of the population lying within ±1SD and 90 percent within ±1.5SDs of the mean. Less than one percent were more than +2SDs and just under four percent more than −2SDs. The distribution was virtually identical in Russia and Belarus, with 80 percent of the population falling within ±1SDs, slightly skewed to the positive, with the minimum being −3.9 and the maximum in Belarus +2.7 and +2.3 in Russia. The minimum in Ukraine was −4.2 and the maximum +2.2, with nearly 30 percent of the population being more than −1SD from the mean (and 10 percent −2SDs) and only 10 percent more than +1SD. This suggests that social quality is poorer in Ukraine than in Belarus and Russia and that the vast majority of the population in all three countries share a poor quality of life, with some having an extremely poor one and only a few experiencing a better quality of life

In this paper we have used the Social Quality model, a model derived from sociological theory, to explore the relationship between the economic and social impact of the transformation in the former Soviet Union. The model specifies both the conditions for well-being and the conditions for building and sustaining societies that are able to ensure the well-being of their members. We have shown, using qualitative and quantitative data, that a majority of the population have a poor quality of life and good reason to be dissatisfied with their lives. There is a lack of economic security, social cohesion, social integration into the wider society and the conditions for empowerment, leaving many unable to develop capabilities in order to adequately function (Sen 1993). The one remaining source of security for many is the support they get from close family and friends – some do not even have this. What is perhaps surprising is the importance of the physical and psychological conditions for empowerment (physical and psychological health and feeling in control and having influence) for well-being. However, the model specified the conditions for constructing the space for a liveable society, and without improvements in the economic circumstances of a majority of citizens there is unlikely to be an increase in subjective well-being. Material security and social cohesion provide the structure within which individuals can build social relations, take control of their lives and have good physical and psychological health.

Objectively the transformation has had a direct impact on the health, wealth and quality of life in all three countries. The majority are ‘loser’ with only a small number of ‘gainers’. They are aware of this and dissatisfied, but also feel at a loss to know how to change the situation. The transition has also involved a change in ideology – from one where the collective was emphasised to one based on individual self-reliance and responsibility, but in circumstances where many feel that they cannot take responsibility for their lives.

Thus, in understanding the impact of the transition on citizens it is necessary to understand individuals’ place in the sociological sense of their location within the opportunity structures (re) created. A connection has to be made between these larger societal changes – generative mechanisms – and their social consequences. Analytically this involves making a distinction between system integration or disintegration and social integration or disintegration. Theories of transition and transformation centre mainly on the former instance on changes, emphasising structural changes in the economic or political situation. Here we have tried to go beyond such explanations by exploring relationships of social integration and including the role of agency as well as structure. Explorations at this level of analysis can give rise to middle-range typologies which model societal transitions, taking into account the role factors at the level of the social and at the level of subjective well-being, since the capabilities of individual agents to act are embedded in their social as well as material circumstances.

Fear of crime

Computed from: are you not worried at all, not very worried, somewhat worried, worried about: having things stolen from home; being harassed or threatened on street; being robbed on the street. (Chronbach's alpha) CA: 70

Satisfaction with political development

Computed from: how satisfied are you with … very satisfied, satisfied, dissatisfied, very dissatisfied: the way democracy developing; economy developing,; education system; social security’ system; government performs duties in national office; local authorities solving region's affairs; health system. CA: 0.80

Political influence

Computed from agrees, quite agree, rather disagree, disagree: have an influence on national government; have an influence on regional government; take an interest in politics. CA: 0.74

Trust government

Computed from to what extent do you personally trust … great trust, quite trust, rather distrust, great distrust: president of country; national government; regional government; political parties. CA: 0.88

Trust institutions

Computed from To what extent do you personally trust … great trust, quite trust, rather distrust, great distrust: courts; police; army; trade Unions. CA: 0.78

Social resource

Computed from If you had any of the following problems, is there anyone you could rely on to help you from outside your own household … yes/no/not-sure: someone to rely on if feeling depressed; someone to rely on if need help finding a job someone to rely on if need to borrow money to pay urgent bill. CA: 0.7

Personal support

Computed from Here are a few questions about people in your life who can provide you with help or support … yes/no/not sure: someone can really count on to listen when you need to talk; someone can really count on to help you out in a crisis; someone you can totally be yourself with; someone you feel appreciates you as a person; someone can really count on to comfort you when upset. CA: 0.89

Malaise

Computed from Have you recently experienced the following: unable to concentrate; insomnia; felt under constant strain; often shaking and trembling; frightening thoughts; spells of exhaustion/fatigue; feelings of stress; feeling lonely; loosing confidence in self. CA: 0.77

Control

Computed from Have you recently experienced the following? felt unable to overcome difficulties; unable to enjoy normal daily activities; dissatisfaction with work; unable to influence things; that life is too complicated. CA: 0.70

Life Satisfaction Index

Computed from General Satisfaction (how satisfied you are, all things considered with your life as a whole, definitely satisfied, quite satisfied, rather dissatisfied, definitely dissatisfied, don't know, refused) and Happiness (talking all things together, how would you say things are these days – would you say you are, very happy, pretty happy, not too happy, very unhappy, don't know, refused).

Pamela Abbott Ac SS is an honorary professor in the School of Social Sciences, University of Aberdeen, and senior research associate, Institute of Policy Analysis and Research-Rwanda, Kigali, Rwanda.

Claire Wallace Ac SS is Director of Research and Commercialisation, College of Arts and Social Sciences, University of Aberdeen, and professor of sociology.