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  • Income situations, income conditions among the residents of two settlements
    45-54
    Views:
    200

    The monthly net income of settlement residents is much lower than in the town of Nyíregyháza or nationwide. Poor employment stands in the background, which naturally stems from the education level of settlement residents. Almost 80% of them completed 8 grades of primary school only or even fewer, while the number and rate of those who gained any qualification is very low. When examining income disparities in Nyíregyháza, it can be seen that the majority of settlement residents, 76.6%, belong to the 2 lowest deciles, and the rate of income poor also exceeds what is measured in the town or across the country. Considering the 60% of median income, 78% of the residents are poor. Regarding the costs of living, housing expenses cause the biggest trouble and many households have been struggling with arrears.

  • Housing in a slum
    76-89
    Views:
    149

    The study analyses the quality of life of the inhabitants of the Roma housing estate through the housing conditions. The housing estate has undergone several changes in the last two years, but the segregation character of the estate has not changed. There is the mobility of residents moving in and out of the settlement, and one-third of the population has moved in from other settlements that have been demolished in the last two years. The exterior and refurbishment of the residential buildings on the site have renewed the housing stock and the residents are now living in comfortable rental accommodation. However, housing poverty persists. Residents live mainly in small and overcrowded flats where children usually share a room with adults. The rising cost of housing maintenance is a serious problem for payment in the settlement. Although the condition of the housing has improved with renovations in the settlement, the increase in overcrowding and housing costs has not brought an increase in the standard of living in terms of housing.

  • A digitális egyenlőtlenség vizsgálata a társadalmi kirekesztődés szempontjából
    67-81
    Views:
    588

    My research, which is part of a doctoral thesis, was made in Bereg the most backward subregion of Hungary in 2017. I examined the risk of poverty and social exclusion concerning the children of the age of 14 living here. I looked at this risk from a new angle, the angle of digital inequality. I looked for the answer whether the usage of the modern multi-media devices and the internet can help in the development of this subregion, the future generation will be able to meet the exigencies of the time, find a job in the digitalized labour market. Or else, the lack of these devices and the disability of using them make their position worse. I unveiled the students’ sociodemographic, socioeconomical features, the degree of the supply concerning multi-media devices, the purpose of their usage, their attributes and the factors causing digital inequality. I scrutinized the degree of ICT usage at schools, the relationship between the usage of the internet and the school achievements, the students’ relationships and their future prospects. In this article I would like to introduce the first part of my research in which I examined the socioeconomical background of the degree of supply with multimedia devices.

  • Situational pictures of settlements
    19-31
    Views:
    340

    Within the research into the life quality of Roma people residing in settlements, this study analyzes their housing situation using the available data. Although the Husar and the Eastern settlements are separate ones situated at the most distant ends of the city of Nyíregyháza, they show similarities regarding the number and condition of flats, housing environment and the housing quality of the residents. Housing poverty is palpable in both settlements which can be described with no restoration of buildings or flats for many decades, hazards in the environment and hardly affordable housing costs. This study presents the details and tries to understand the picture behind the data.