The research aims to explore the degree of acceptance of digital work culture among the youth in the Emirati society within the study sample. Additionally, it aims to reveal the relationship between “gender” and “educational status” as sociodemographic factors among the youth in the study sample and their level of acceptance of digital work culture. Furthermore, the study aims to identify prospective trends in digital work culture among young individuals in Emirati society. Due to the nature of the descriptive research, it employed the “sample social survey” approach. The field study primarily utilized a quantitative tool for data collection, namely the “digital questionnaire.” This questionnaire was administered to a purposefully chosen random sample comprising young individuals actively seeking employment opportunities (unemployed individuals) or those new to the labor market. The participants fell within the age group of 15 to 35 years, totaling 184 individuals. Care was taken to ensure that this sample was representative of all youth categories in Emirati society, considering demographic factors such as gender, place of residence, and educational status. The research findings indicate that an overwhelming majority of young individuals in the study sample (97.8%) have no obstacles to accepting job opportunities that necessitate digital and technological skills. Moreover, the study uncovered a direct and statistically significant relation between “gender” and the “level of acceptance of digital work culture,” favoring females. This implies that females are more inclined to accept digital job opportunities compared to males. Additionally, the results highlighted a positive and statistically significant relation between both “educational status” and the “level of acceptance of digital work culture.” In other words, individuals with higher levels of education demonstrate a greater interest in digital job opportunities. Utilizing Step-wise Regression, the study also made predictions about the spread of “future digital work culture” in the United Arab Emirates based on the variable of “education.”

The Human Development Index, which accounts for both net foreign income and the total value of goods and services generated domestically, illustrates how income becomes less significant as Gross National Income (GNI) rises by using the logarithm of income. South Africa ranks 109th out of 189 countries in the Human Development Index (HDI) within the Brazil, Russia, India, China and South Africa (BRICS) economic bloc, raising long-term sustainability concerns. The study explores the relationship between economic, demography, policy indicators and human development in South Africa. South Africa’s unique status as a developing country within the BRICS economic group, alongside its lengthy history of racial discrimination, calls for a sophisticated approach to understanding Human Development. Existing research considered economic, demography, policy indicators independently; the gap of understanding their interconnection and long-term effects in the South African contexts exists. The study addresses the gap by using Autoregressive-Distributed Lag (ARDL) approach to investigate the short-term and the long-term relationship between economic, demography, policy indicators and human development in South Africa. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa. The findings indicate that growth in GDP is a key factor in the HDI since it shows that there are more financial resources available for human development. By discovering these links, the study hopes to provide useful insights for policymakers seeking to promote sustainable human development in South Africa.

Research indicates a strong correlation between sociodemographic factors and success in learning to read. This study examines the sociodemographic characteristics of 1131 preschool and 1st-grade children in Portuguese public schools and explores the relationship between these characteristics and key competencies for reading acquisition. The collection included a sociodemographic questionnaire and pre-reading skills, such as letter-sound knowledge. To assess the relationship between the sociodemographic variables and the letter-sound knowledge, inter-subjects (parametric and non-parametric) difference tests were conducted, as well as correlation analyses. To understand whether letter-sound knowledge is predicted by sociodemographic variables, a multiple linear regression analysis was performed using the Enter method. The results suggest that the mother’s education is the variable that most strongly contributes to success in reading acquisition. Socioeconomic status and the type of school also play a role in reading achievement. Identifying the sociodemographic factors that most strongly correlate with reading acquisition success is crucial for a more accurate identification of at-risk children and to provide targeted support/inclusion in reading skills promotion projects.