Lone mothers and child support receipt in 21 European countries

With increasing trends in divorce, separation and multi-partner fertility, more families have become subject to child support policies. This paper explores child support receipt in 21 European countries using 2017–2018 European Union Statistics on Income and Living Conditions data. We investigated: (1) cross-country differences in the prevalence and amount of child support received and (2) the determinants of child support receipt among lone mothers across countries. We found that the proportion of lone-mother families receiving child support ranged from 16 per cent in Luxembourg to 75 per cent in the Czech Republic, with large variations in the amount of child support received. Our results suggested that the socioeconomic characteristics of lone mothers, including marital status, education, employment status, number of children and income, were associated with the likelihood of receiving child support in most countries but these associations varied significantly across countries.

Implications of COVID-19 Vaccine Hesitancy: Results of Online Bulletin Board Interviews

Reluctance to accept vaccination against COVID-19 poses a significant public health risk and is known to be a multi-determined phenomenon. We conducted online focus groups, or “bulletin boards,” in order to probe the nature of COVID-19 vaccine hesitancy and its implications. Participants were 94 individuals from three distinct U.S. geographical areas and represented a range of demographic and socioeconomic characteristics. Six themes emerged from the 3 day-long bulletin boards: the most trusted source of health information sought is the personal physician; information about health is nevertheless obtained from a wide variety of sources; stories about adverse side effects are especially “sticky”; government health institutions like CDC and FDA are not trusted; most respondents engaged in individualistic reasoning; and there is a wide spectrum of attitudes toward vaccination.

A Predictive Model of Pandemic Disaster Fear Caused by Coronavirus (COVID-19): Implications for Decision-Makers

This paper presents quantitative research results regarding a predictive model of pandemic disaster fear caused by the coronavirus disease (COVİD-19). The aim of this paper was to establish the level and impact of certain demographic and socioeconomic characteristics on pandemic disaster fear caused by the coronavirus (COVID-19). The research was conducted using a questionnaire that was provided and then collected online for 1226 respondents during May 2021. A closed, five-point Likert scale was used to create the structured questionnaire. The first section of the questionnaire included research questions about the participants’ socioeconomic and demographic characteristics, while the second section included issue questions about fear caused by COVID-19. The results of multivariate regression analyses showed the most important predictor for fear of COVID-19 to be gender, followed by age and education level. Furthermore, the results of t-tests showed statistically significant differences between men and women in terms of different aspects of pandemic disaster fear caused by the coronavirus disease. Our results have several significant public health implications. Women who were more educated and knowledgeable, married, and older, reported a greater fear of the outbreak at various levels. Decision-makers can use these findings to identify better strategic opportunities for pandemic disaster risk management.

Occupation and COVID-19 diagnosis, hospitalisation and ICU admission among foreign-born and Swedish-born employees: a register-based study

BackgroundResearch on occupation and risk of COVID-19 among foreign-born workers is lacking. We investigated whether working in essential occupations was associated with COVID-19 diagnosis, hospitalisation and intensive care unit (ICU) admission and whether foreign-born workers in similar occupations as Swedish-born individuals had a higher risk of the studied outcomes.MethodsOccupational data (2018–2019) of 326 052 employees (20–65 years) who were resident in Sweden as of 1 January 2020 were linked to COVID-19 data registered from 1 January 2020 to 28 February 2021. We analysed the risk of COVID-19 outcomes in different occupational groups and in four immigrant/occupation intersectional groups using Cox proportional hazards regression with adjustments for sociodemographic and socioeconomic characteristics and pre-existing comorbidities.ResultsWe identified 29797, 1069 and 152 cases of COVID-19 diagnosis, hospitalisations and ICU admissions, respectively, in our cohort. Workers in essential occupations had an elevated risk of COVID-19 diagnosis, hospitalisation, and ICU admissions. Healthcare workers had a higher risk of all the outcomes compared with other essential workers. Relative to Swedish-born workers in non-essential occupations, foreign-born workers in essential occupations had 1.85 (95% CI 1.78 to 1.93), 3.80 (95% CI 3.17 to 4.55) and 3.79 (95% CI 2.33 to 6.14) times higher risk of COVID-19 diagnosis, hospitalisation and ICU admission, respectively. The corresponding risks among Swedish-born workers in essential occupations were 1.44 (95% CI 1.40 to 1.49), 1.30 (95% CI 1.08 to 1.56) and 1.46 (95% CI 0.90 to 2.38).ConclusionOccupation was associated with COVID-19 outcomes and contributed to the burden of COVID-19 among foreign-born individuals in this study.

A Service-Oriented Foundation for Big Data

This paper provides a service-oriented foundation for big data. The foundation has two parts. Part 1 reveals 10 big characteristics of big data. Part 2 presents a service-oriented framework for big data. The framework has fundamental, technological, and socio-economic levels. The fundamental level has four big fundamental characteristics of big data: big volume, big velocity, big variety, and big veracity. The technological level consists of three big technological characteristics of big data: Big intelligence, big analytics, big infrastructure. The socioeconomic level has three big socioeconomic characteristics of big data: big service, big value, and big market. The article looks at each level of the proposed framework from a service-oriented perspective. The multi-level framework will help organizations and researchers understand how the 10 big characteristics relate to big opportunities, big challenges, and big impacts arising from big data. The proposed approach in this paper might facilitate the research and development of big data, big data analytics, business intelligence, and business analytics.

Family farm succession: evidence from absorptive capacity, social capital, and socioeconomic aspects

Farm succession is a process socially built from the preparation of the successor and the farm to meet a family business’ expectations. This study aimed to identify how social capital, absorptive capacity, and socioeconomic characteristics influence farm succession. The survey was conducted sampling 82 soybean and corn Brazilian farmers. The questionnaire measured socioeconomic characteristics, Absorptive Capacity (AC), and Social Capital (SC). To test the influence of AC, SC, and socioeconomic characteristics on farm succession, Spearman correlation coefficient (rs) was performed. Results showed that the absorptive capacity can influence farm succession through acquisition, assimilation, use, and transformation of external knowledge into decision making, supporting the definition of successors. Results also suggested that social capital plays an important role to form relationship networks, stimulating discussions, and supporting the designation of successors. The socioeconomic characteristics ‘percentage of family income from the farm, participation in courses and lectures, and being a cooperatives member’ also presented a significant positive correlation with farm succession. Issues related to the capacity to absorb external knowledge, social and symbolic capital and generational transference can be fundamental in the continuity of the family farming business.

MOBILE PASTORALISM AND SOCIO-ECONOMIC DEVELOPMENT AMONG RURAL FULANI COMMUNITIES IN KWARA STATE, NIGERIA

This study makes a spatial analysis of mobile pastoralism and socioeconomic problems among rural Fulani communities in Irepodun Local Government Area of Kwara State, Nigeria. Specifically, the study assesses the socioeconomic characteristics of mobile pastoralists; identify the length of stay of mobile pastoralists in their host communities and identify socioeconomic problems confronting Fulani herdsmen in their economic activities. A multistage sampling technique was employed to sample 740 Fulani herdsmen from twenty Fulani settlements and from four adjoining villages. Descriptive statistical techniques such as tables cross tabulations, percentages and graphs were employed to analyze the demographic characteristics of the pastoralists, length of stay in their host communities and other sources of income. Matrix scoring was used to rank the socioeconomic problems identified. The results revealed that the mean average age of sampled respondents was 44.8years, 83.8% married and average household size of 11people. Dwindling pasture, land degradation and drought were the most pressing socioeconomic problems identified. The study concludes by recommending adult education for the Fulani pastoralists as this will assist in enhancing and improving the socio-economic life of the mobile pastoralists.

The effects of state coercion on voting outcome in protest movements: a causal forest approach

In this research note, we examine how Hong Kong voters respond to police violence in the recent social movement. We use causal forests, a machine learning algorithm, to estimate the impact of tear gas usage specific to each constituency. Based on the 2019 District Council Election outcome, we find that there is heterogeneity in the effect of state coercion on the vote share of pro-democracy candidates, depending on many socioeconomic characteristics of the constituency. The results imply that economic concerns still matter in the struggle to obtain democracy: citizens who sense economic insecurity in social unrest show less disapproval of state violence.