Social stratification of households in the context of the digital divide

. To study issues of social deprivation and inequality, scientists explore factors, correlations and various indices and models. The deprivation indices are used in many countries to target interventions and policies to populations with the greatest needs. The aim of this research is to construct stratification scale of Russian households for the period of Covid-19 pandemic to study their social deprivation. The data source for household social deprivation is the Russian Longitudinal Monitoring Survey (RLMS-HSE). The results show that the digital divide of households in extreme poverty greatly increases their social exclusion and increases social deprivation. About 50% of extremely poor households live in rural areas. It confirms the ongoing income stratification of urban and rural residents. About 30% of households do not own a car. In the context of the restrictions of the self-isolation regime, this is a significant factor in social exclusion. Low incomes and material deprivation do not allow such households to change this situation. Even not all rich households have access to high-speed Internet. This may be due to the underdevelopment of high-speed Internet infrastructure.


Introduction
To study issues of social deprivation and inequality, scientists explore factors, correlations and various indices and models.Area-based deprivation indices are used in many countries to target interventions and policies to populations with the greatest needs.In one research authors examine the specificity and sensitivity of deprivation indices across Great Britain in identifying individuals claiming income-and employment-related social security benefits.Across all indices, the sensitivity and specificity for detecting income-and employmentdeprived individuals were low, with less than half living in the most deprived 20% of areas.Between 55% and 62% of income-deprived people and between 56% and 63% of employment-deprived people were missed across the indices at the 20% deprivation threshold.Area-based deprivation measures in Great Britain have limited sensitivity and specificity for identifying individuals who are income or employment deprived.Placebased policies and interventions are unlikely to be effective at reducing inequalities as a result.Creation of individually linked data sets and interventions that recognise the social and economic relationships between social groups are likely to be more effective.[1] Researching social needs is fundamental for understanding the dynamics of quality of life, social exclusion, poverty or economic inequality, as well as for the design of social policy.In Romania, research on social representations of the good life has shown that people make a distinction between the material and social world.The material aspirations could be analyzed on two dimensions: a) fundamental needs, essential for survival, which are universal and have an internal source and b) material needs that reflect the social circumstances in which people live in.Material deprivation is multi-dimensional, affecting variable segments of the population.The most important factors accounting for the variance in material deprivation are income, labour market participation, education and medium of residence.[2] Another paper aims the decomposition of the multidimensional Gini coefficient by deprivation to investigate how aggregate multidimensional poverty inequality translates into inequality within each of its components.The different social policies to reduce multiinequalities must mainly be oriented towards health policies and access to drinking water, which are unequally distributed during the three periods.And social policies to reduce inequality in education, sanitation and housing are also to be taken into account.[3] Luis Ayala, Javier Martín-Román and Carolina Navarro analyzed how material deprivation responds to drastic changes in unemployment levels.They explored unemployment shocks registered in some European Union countries during the so-called Great Recession.As a result they found that contrary to the traditional assumption of the low sensitivity of material deprivation measures to changes in the economic cycle, unemployment shocks have a significant and rapid impact on material deprivation.This conclusion holds even when extending the period of analysis, changing the indicator of material deprivation, or modifying the definition of unemployment shock.[4] G. McCartney and R. Hoggett tried to compare the sensitivity of the Scottish Index of Multiple Deprivation (SIMD) for detecting income and employment deprived individuals by urban-rural classification and across local authorities.As a result they found that the number and percentage of income and employment deprived people is higher in urban than rural areas.The SIMD misses a higher percentage of income and employment deprived people in remote, rural and island areas across deprivation thresholds and irrespective of whether national, local or within urban-rural classification strata are used.The absolute number of income and employment deprived individuals is greater in urban areas across rankings and thresholds.[5] In another research authors analyzed the degree of housing deprivation faced by households in European countries when COVID-19 lockdown measures were enacted.They found similar orderings of housing deprivation dimensions by country with the highest degree of deprivation in the living space dimension and the lowest one in the standard housing or technology deprivation dimension.Nonetheless, housing deprivation levels differ across countries, with Eastern European households being significantly more housing deprived than the rest when the lockdown began.This result shows that the effects of the lockdown on social well-being have not affected all Europeans equally and emphasizes the need for government measures that promote decent housing.[6] Another study used data from the 2017 Chinese General Social Survey to explore the mechanism through which migrants' home ownership or non-ownership in the migration process affects their sense of relative deprivation.To do so, a ranked regression and parallel multiple mediation model were developed.Additionally, a heterogeneity analysis was conducted to account for the region in which migrants lived and their age.The results revealed that home ownership significantly reduced migrants' relative deprivation.Moreover, the perception of economic and symbolic capital was found to play a role in the effects of wealth and class, respectively.[7] In another paper the relationship between disadvantaged social status and adverse health outcomes within a context-contingent thesis of relative deprivation.Authors argue that the health effect of low relative status depends on contextual status homogeneity, which is measured as income inequality and group diversity.Applying mixed-effect modelling to the pooled 2011-2013 Chinese General Social Survey and exploring the cross-level interactions, they found that 1) people in the bottom socioeconomic quartile report significantly better health when contextual income inequality is lower; 2) racial-ethnic minorities report significantly better health when contextual ethnic diversity is higher; and 3) religious minorities also report significantly better health when contextual religious diversity is higher.[8]

Method
To assess social deprivation, stratification scales are built.They include five intervals.In total, three sub-scales and one integral scale are constructed.On the first sub-scale, all households included in the survey are distributed according to income, on the second subscale -according to the possession of socially significant assets, on the third sub-scaleaccording to the digital divide.
To rank households on the first private scale, the indicator of per capita income is used.The division of the scale into intervals begins with the determination of the middle of the third interval.It is the value of the median income.Further, the boundaries of the intervals on the scale are determined with a step of 0.4 from the middle of the third interval.The boundary between the first and second intervals, which ranks all households into poor and non-poor is set at 50% of the median income.[9] As a result, the first partial scale has five intervals separated by four boundaries.
For the second sub-scale, the indicator of the socially significant assets is used.It makes possible to draw a conclusion about the well-being of the household.Among such assets are the ownership of first housing, the ownership of additional housing, the ownership of one or more cars and the presence of a land plot owned by the household.[10] The possession of all four assets allows the household to fall into the fifth interval of the scale, the presence of three assets -into the fourth interval, the presence of two assets -into the third interval, the presence of at least one asset -into the second interval.The absence of all the above mentioned assets in a household corresponds to the first interval.
For the third sub-scale, the indicators of the digital divide are used.It makes possible to draw a conclusion about the digital inclusion of the household.Among such indicators are the possession of a computer or laptop, the availability of Internet access, the availability of cable/sputnik TV and the use of mobile cellular services.The presence of all four indicators allows the household to fall into the fifth interval of the scale, the presence of three indicators -into the fourth interval, the presence of two indicators -into the third interval, the presence of at least one indicator -into the second interval.The absence of all the above mentioned indicators in a household corresponds to the first interval.
The construction of an integral scale of social deprivation starts from assigning each household a score corresponding to the number of the interval on each of the three subscales in which this household fell.Suppose the household is in the fifth interval of the scale, then it is awarded five points.Next, the scores on the three sub-scales for each household are summed up, and we get the ranking of households in the following groups: group 1 -extreme poor (1-3 points); group 2 -needy (4-6 points); group 3 -middle class (7-9 points); group 4 -prosperous (10-11 points); group 5 -rich (12 points).As a result, each interval corresponds to a specific social group of households.The most vulnerable social group in this ranking is in the first interval.It experiences deprivation not only in terms of income, but also in the possession of socially significant assets and in the digital inclusion.Thus, a social stratification of households from the richest to the extremely poor is built.
The data source for household social deprivation is the Russian Longitudinal Monitoring Survey (RLMS-HSE).[11] The survey is carried out on an internationally recognized methodology on a regular basis and covers the entire territory of Russia.The sample of households ensures the representativeness of the study.

Findings
Table 1 presents the ranking of households according to a first sub-scale of social deprivation -income sub-scale.In 2019, 5% of households (7.6% of individuals) were in the lower income distribution with an average per capita income of 5.3 thousand rubles.In 2020, during the Covid-19 pandemic, the number of such households decreased by 1% (1.5 individuals).This may be due to government measures to support families, the unemployed, the disabled and working pensioners.However, the incomes of the households remaining in the first interval in 2020 practically did not grow.This made them more vulnerable to restrictions during the period of self-isolation.The increase in 2020 of households that fell into the middle third interval occurred simultaneously due to an increase in the income of low-income households and a decrease in the income of high-income households.The number of households in the upper fourth and fifth intervals decreased by 2%.Traditionally, the lower first and second intervals contain a large number of households living in rural areas.This confirms the ongoing income stratification of urban and rural residents.Table 2 presents the ranking of households according to a second sub-scale of social deprivation -sub-scale of assets.There were no significant changes in the ranking of households on the sub-scale of assets from 2019 to 2020.The number of households in the fourth interval decreased by 1.1%.
The number of households in the second interval increased by 1.3%.This indicates a decrease in the provision of households with socially significant assets.Perhaps these assets are sold to replenish the financial budget of households or due to the impossibility of maintaining them.It should be noted that about 30% of households do not own a car.In the context of the restrictions of the self-isolation regime, this is a significant factor in social exclusion.Low incomes and material deprivation do not allow such households to change this situation.Table 3 presents the ranking of households according to a third sub-scale of social deprivation -sub-scale of digital inclusion.The number of households in the digital divide decreased from 2.8 to 2.1% in 2020.These households do not have a computer, Internet access, mobile communications and cable/satellite television.At the same time, the number of households with access to all digital resources and falling into the fifth interval of the scale increased by 2.8%.However, even in this fifth interval, not all households have access to high-speed Internet.This may be due to the underdevelopment of high-speed Internet infrastructure.There were no significant changes in the social stratification of households from 2019 to 2020.The average income slightly increased in all groups of households, except for those in the fourth interval.The number of households with access to the Internet increased in 2020 in all intervals of the stratification scale except for the first interval.In the first interval, a decrease of 1.4% was recorded.In the context of the Covid-19 pandemic, this digital divide of households in extreme poverty greatly increases their social exclusion and increases social deprivation.

Conclusion
In the context of the Covid-19 pandemic, the digital divide of households in extreme poverty greatly increases their social exclusion and increases social deprivation.About 50% of extremely poor households live in rural areas.It confirms the ongoing income stratification of urban and rural residents.About 30% of households do not own a car.In the context of the restrictions of the self-isolation regime, this is a significant factor in social exclusion.Low incomes and material deprivation do not allow such households to change this situation.Even not all rich households have access to high-speed Internet.This may be due to the underdevelopment of high-speed Internet infrastructure.

Table 1 .
Ranking of households by per capita income, 2019-2020

Table 2 .
Ranking of households by a set of socially significant assets, 2019-2020