This study aims to examine policy direction and support with focus on the characteristics, effectiveness, influence, and ripple effects of local governance in social welfare. The purpose of the study is as follows. First, we examined the characteristics of social welfare governance by investigating the structure and management status of local governance in the social welfare sector. Second, we examined the actual state of activities, performance and influence of the Community Welfare Association (si-gun-gu and eup-myeon-dong) as a representative governance and suggested tasks for the growth of local governance in the social welfare sector. To achieve the goals of this research, the study was composed of the following five parts. First, analysis of actual conditions of the Community Welfare Association (si-gun-gu and eup-myeon-dong) as a key mechanism of local-based governance in the social welfare sector; second, analysis of actual network conditions in local private sectors; third, analysis of international cases of governance in the community social welfare sector; fourth, analyzing the factors for activating the local-based cooperative system (network); lastly, suggestion of a plan for a sustainable public-private partnership system. The results indicated that awareness of the Community Welfare Association is positively changing insted of the awareness of them staying negative (e.g., centered public power, formal management, unclear results), and the Community Welfare Association is growing as a foundation of a healthy local community in providing social welfare. While the work of the Community Welfare Association is organized by the network of the connected local communities as a beginning level, it is simultaneously able to fit in citizen initiative, spontaneity, benefits and public-private partnership, and is indicting changes in values, attitudes, interest toward social welfare such as local solidarity, sense of community, social capital, and self and neighborhood social welfare. Therefore, it is a valuable experience beyond contributing to the social welfare delivery system and suggests that attention and investment in policy should be required for solving multi-dimensional problems in order to develop and expand this experience.
Machine learning is a subfield of the growing research on artificial intelligence (AI). Specifically, it focuses on the development of algorithms and technology that enable computers to learn independently using data. Machine learning, widely regarded as instrumental in advancements in image processing, video and voice recognition, and Internet searches, has proven to be quite effective as a tool for anomaly prediction and detection. Anomaly detection refers to the process by which one finds instances or data, out of a given pool, that diverge from expected patterns. In this study, we define the concept of anomaly detection, after which we apply the anomaly detection methodology to the given sets of health and welfare policy data to perform an exploratory analysis. We discuss the issues involved in the application of anomaly detection and summarize the policy implications. The data subjected to our analysis include the fludeoxyglucose positron emission tomography (FDG-PET) data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), regarding health, and the results of the Elderly Survey 2017.
Using twelve waves of data from the Korean Welfare Panel Study (2006-2017), we evaluate mechanisms linking employment type to various health outcomes, including depression, self-esteem, and self-rated health with a focus on differences between standard and other types of employment. Guided by prior research, we examine several mechanisms such as economic insecurity and psychosocial stressors, using fixed-effects models that control for unobserved time-invariant individual heterogeneity. Our findings confirm the importance of selection in that much of the association between employment type and health observed in simple cross-sectional OLS models loses significance in fixed-effects models. We also find supporting evidence for the mediating role of economic insecurity and psychosocial stressors. For instance, the lower levels of satisfaction in job and life conditions help explain lower self-esteem of male nonstandard workers relative to standard workers. It is also interesting that the hypothesized mediators often suppress the relationship between employment status and health in which a significant relationship is revealed only when the specific mediator is taken into account. Findings of this study will shed valuable insights on the pathways in which specific employment types affect men’s and women’s health outcomes.
The National Health Insurance has been expanding its coverage with a view to helping households ease their economic burden of illness. Concerns remain, however, that social health safety nets as they stand do not sufficiently prevent impoverishment due to illness.
The 23rd Global Social Security Forum: The Challenges and Role of Poverty Policy: Brazil and the UK's Experience in Focus11 December 2019 - 1:00 p.m. to 5:30 p.m.Brahams Hall(19th Floor), Hotel President, SeoulHosted by Sejong Welfare Foundation and the Korea Institute for Health and Social Affairs Program 13:00-13:20 Registration 13:20-14:00 Presentation: Poverty and Anti-Poverty Policy in the UK, David Gordon, Professor, University of Bristol 14:00-14:30 Presentation: The Impact of Universal Credit on the Debts of the Poor in the UK, Rod Hick, Professor, Cardiff University 14:30-15:00 Discussion Moderator: Moon Jin-Young, Professor, Sogang University Discussants: Kim, Ki-tae, Associate Research Fellow, KIHASA; Jung Yun-Tae, Senior Research Fellow, Sejong Welfare Foundation; Choi Young Jun, Professor, Yonsei University 15:00-15:30 Coffee Break 15:30-16:00 Presentation: Brizilian Poverty Policy, Ana Paula Matias, Directory Technical Advisor, National Secretariat for the Promotion of Human Development 16:00-16:30 Presentation: Social Protection and Family Benefit in Brazil, Joana Mostafa, Research Specialist, Institute for Applied Economic Research of the Federal Government of Brazil 16:30-17:00 Presentation: History of Social Security in Brazil, Martene Santos, Professor, University of Brasilia 17:00-17:30 Discussion Moderator: Lee Chang Gon, President, Hankyoreh Economy & Society Research Institute Discussants: Kwak Yoonkyung, Associate Research Fellow, KIHASA; Won Il, Research Fellow, Sejong Weflare Foundation; Lee Jeong-Hee, Research Fellow, Korea Labor Institute
The 5th Inclusive Welfare Forum: Income Distribution Trends and the Challenges Facing the Inclusive StateNoori Ballroom II(6th Floor), Four Seasons Hotel, SeoulHoted by the Korea Institute for Health and Social Affairs Program 10:00-10:30 Registration 10:30-12:00 Morning Session Moderator: Nam Chan Seop, Vice Chair, Korea Association of Social Welfare Policy Presentation: Income Distribution Trends in Japan and Their Implications for Korea, Lee Kang Kuk, Professor, Ritsumeikan University Presentation: Income Distribution Trends and the Directions of Redistribution Policy, Choo Byung Ki, Professor, Seoul National University Discussants: Lee Seung Yoon, Professor, Ewha Womans University; Lee Won Jin, Associate Research Fellow, KIHASA; Choi Yoo Seok, Professor, Hallim University 12:00-13:30 Lunch 13:30-14:00 Opening Remarks: Cho Heung-seek, President, KIHASA Congratulatory Remarks: Park Neung-hoo, Minister of Health and Welfare; Kim Yeon Myung, Chief Social Policy Advisor, Office of the President 14:00-14:50 Keynote Speech Conditions for Sustainable Inclusive Policy: the Nordic Model, Choi Yeon Hyuk, Professor, Linnaeus University, Sweden 14:50-15:10 Coffee Break 15:10-16:40 Afternoon Session Moderator: Seok Jae Eun, Chair, Korea Association of Social Welfare Policy Presentation: Inequality in the UK: the Limitations of the Selective Welfare State, Jeong Hee Jeong, Kent University, UK Presentation: Diagnosing Innovative Inclusive State: the Future Direction of Social Policy , Choi Young Joon, Yonsei University Discussants: Choi Han Soo, Professor, Kyungbook National University; Kim Ki Tae, Associate Research Fellow, KIHASA, Kim Jin Wook, Professor, Seogang University 16:40-16:50Coffee Break 16:50-18:00Wrap-up Discussion