Can you help me write my thesis paper? Can you write me… 1. analysis part 800-900 words 2. abstract/introduction 500 words based on the draft of my paper? I will explain them in detail after I hir

Can you help me write my thesis paper? Can you write me… 1. analysis part 800-900 words 2. abstract/introduction 500 words based on the draft of my paper? I will explain them in detail after I hir
Lee 28 Name (student ID#: ) Advanced Seminar E-5 ILA Fall 2022 Governance of Disaster-Vulnerable Classes in the COVID-19 Pandemic: A Comparative Analysis of Public-Health and Welfare Governance Policy 3. Methodology 3.1 Research questions, hypotheses, and design This study aims to examine how public-health governance and welfare governance for the disaster governance for the disaster-vulnerable class are implemented in the COVID-19 pandemic. Thus, this study presents the following research questions (hereafter RQ): How has public-health governance been implemented in the four countries, South Korea, Japan, the United Kingdom, and USA, during the COVID-19 pandemic? (RQ 1); How has welfare governance for disaster-vulnerable groups in the four countries changed throughout the pandemic? (RQ 2); What is the desired direction for public health governance and welfare governance in the post-COVID era? (RQ 3). For these research questions (RQ1, RQ2), I first examined whether there was a relationship between deaths related to COVID-19 in each country using the social vulnerability index. This is because Mah and Andrew (2022) reported that the Social vulnerability index could be considered a pragmatic tool for COVID-19 policy and beyond.1 Social vulnerability is a term that describes how resilient a community is when confronted by external stresses on human health. External stresses can range from natural or human-caused disasters to disease outbreaks. By minimizing social vulnerability, we can reduce both human suffering and economic losses.2 The Social Vulnerability Index (SVI) uses U.S. Census data to determine the relative social vulnerability of every census tract. The SVI ranks each tract on 15 social factors (Table 1) and groups them into four related themes. Each tract receives a separate ranking for each of the four themes, as well as an overall ranking. “Socioeconomic status” consists of 4 factors such as below poverty, unemployed, income and no high school diploma. “Household composition & disability” consists of 4 factors such as aged 65 or older, aged 17 or younger, civilian with a diability and single-parent housholds. “Minority status & language” consists of 2 factors such as minority and aged 5 or older who speaks English (or their native language) “less than well.” “Housing type & transportation” consists of 5 factors such as multi-unit structure, mobile homes, crowding, no vehicle, and group quarters.3 Table 1. Components for Social Vulnerability Index Theme Category Subcategory Overall Vulnerability Socioeconomic Status Below poverty Unemployed Income No high school diploma Household Composition & Disability Aged 65 or Older Aged 17 or Younger Civilian with a Disability Single-Parent Households Minority Status & Language Minority Aged 5 or Older who speaks English(or mother tongue) “Less than Well” Housing Type & Transportation Multi-Unit Structures Mobile Homes Crowding No Vehicle Group Quarters Source: CDC (https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html Thus, my research model is shown in Figure 1. In other words, this study examined the effects of the SVI variables (socioeconomic status, household composition & disability, minority status & language, housing type &transportation) on COVID-19-related mortality in each country. Figure 1. Research Model I evaluated the SVI of each country using the Likert 5-point scale (Very poor [5], Poor [4], Neutral [3], Good [2], Very good [1]) after reviewing relevant data on countries registered as UN member states. In addition, COVID-19 mortality data (as of December 1, 2022) of each country announced daily by WHO were collected and the relationship between SVI levels and mortality in each country was analyzed through correlation analysis and multiple regression analysis. My hypotheses are as follows, H1. The worse the socioeconomic status, the higher the COVID-19 related mortality. H2. The worse the household composition & disability, the higher the COVID-19 related mortality. H3. The worse the minority status & language factors, the higher the COVID-19 related mortality. H4. The worse the housing type & transportation factor, the higher the COVID-19 related mortality. 3.2 Data collection and analysis In this study, 43 countries classified as G20 (Table 2)4 among 196 countries under the UN were selected and data related to SVI of these countries were collected from the websites open to the embassies of each country.5 The reason why I selected the countries belonging to the G20 is that they are relatively transparent in releasing data related to SVI, and disclose COVID-19 death statistics without distorting or hiding them like China or North Korea.6 In addition, the combined population of the current G20 members amounts to two-thirds of the world’s population. The sum of these countries’ gross domestic product (GDP) accounts for 85% of the world’s total and accounts for 80% of world trade. Furthermore, it can be said that the policies or agreements decided at the G20 have a very large economic impact internationally.7 For the collected data, I used the SPSS (Ver 30, IBM, USA) statistical program to find the mean and standard deviation, and performed correlation analysis and multiple regression analysis. The statistical significance level was tested at 5%. Table 2. Members of the G20 Region Country Asia Republic of Korea Japan China India Indonesia Saudi Arabia Turkey Europe EU France Germany Italy United Kingdom Russia America Canada Mexico USA Argentina Brazil South Africa Oceania Australia After testing the hypothesis based on the results derived in this regard, the governance related to COVID-19 in Korea, Japan, the United Kingdom, and the United States is examined, focusing on these four main items of SVI. 4. Results 4.1 Descriptive statistics Table 3 and Figure 2 present the mean (5-point Likert scale) and standard deviation of each SVI of the G20 member countries. The average related to H3 (Civilian with a Disability) was the highest (3.26), and the average value of HT3 (Crowding) was measured to be the lowest (1.42). This suggests that while the degree of congestion in residential facilities is generally low in G20 member countries, the vulnerability of people with disabilities is high. In addition, it shows that the share of social vulnerability problems associated with aged 65 or older among the G20 member countries is high (3.16). On the other hand, it is also confirmed that among the G20 member countries, the proportion of social vulnerability problems accounted for by the population under the age of 17 is not very high (1.88). Table 3. Descriptive statistics of variables Figure 2. Bar graph of the mean of the variables Figure 3 shows the communality of each variable and violin plot. Communality refers to common variance that ranges between 0 and 1. Values closer to 1 suggest that extracted factors can explain more of the variance of an individual item.8 The violin plot can show the full distribution of the data; the presence of different peaks and their position and relative amplitude. Thus, violin plots can be used to represent comparison of a variable(or sample) distribution.9 The normal distribution appears in a form in which measurements are collected around the average value and are rarely present at both ends. Therefore, although the measured communality of all variables exceeds 0.5, the reliability of the measured value is low because the distributions of the violin plot of H2, HT3, and HT5 are distorted. Figure 3. Communality and violin plot Figure 4 shows Eigenvalues and screeplot of variables. I performed principle component analysis to check the validity of the variables. As Eigenvalues of 1.0 or greater are considered significant, it is reasonable to group them into four components (Socioeconomic Status, household Composiution & Disability, Minority Status & Language and Housing Type & Transportation), this is confirmed in the accompanying screeplot. Figure 4. Eigenvalue and screeplot 4.3 Correlation analysis Table 4 shows the correlation results of the variables. Mortality variables related to COVID-19 have a correlation of -0.49 with A3 (Mean of Minority Status & Language factors), which is statistically significant (p<0.05). However, other social vulnerability-related variables do not show significant correlations with COVID-19 deaths. Table 4. Correlation analysis 4.4 Multiple regression analysis Table 5 presents the results of a regression analysis on the effects of the four major factors of SVI on COVID-19-related deaths. The effect of A3 (Mean of Minority Status & Language factors) on mortality is that it has a negative relationship (β=-1.32, p<0.05). In other words, in the G20 member countries, the higher the social vulnerability of immigrants and minorities, the lower the death rate. This is judged to be the result of the young age group having a large number of minority immigrants in the young age group. Table 5. Multiple regression analysis (for main factors) SM: Mortality A1: Mean of Socioeconomic Status Factors A2: Mean of Household composition & Disability factors A3: Mean of Minority Status & Language factors A4: Mean of Housing Type & Transportation factors Furthermore, I analyzed the impact of each item of the SVI on COVID-19-related deaths. As shown in Table 6, it was confirmed that S3 (income) positively affects mortality (β=0.6, p<0.05) and M1 (minority) negatively affects mortality (β = -0.4, p <0.1). In other words, it suggests that the COVID-19 mortality rate is high in the vulnerable class with low-income levels in G20 member countries. On the other hand, it shows that COVID-19-related death rates are rather reduced in the minority group (especially immigrants), which is judged to be a bias effect given by young age. Table 6. Multiple regression analysis (for each variable) 4.5 Analysis of SVI in 4 major countries Table 7 presents governance for the socially vulnerable during the COVID-19 pandemic in four major countries, focusing on the four main factors of SVI. Table 7. Analysis of SVI in 4 major countries (focusing on the governance) Category Socioeconomic status Household Composition & Disability Minority status & Language Housing Type & Transportation Republic of Korea – Provision of jobs for low-income people – Implementation of non-face-to-face online education – Disaster relief funds were provided to all citizens. – No additional disaster relief funds were provided for the socially vulnerable. -Vaccination was first offered to the group aged 65 years and over – Visiting nursing care for disabled or elderly patients has become neglected. – Governance for foreigners, a minority, focused on health governance for infectious agents such as immigration control – During the COVID-19 pandemic, housing prices rose significantly, and the government and various organizations focused on stabilizing house prices. – The guarantee of the right to move for the disabled has been an issue so far. – Senior citizen centers and daycare centers where the elderly and infirm are also operated on a limited basis to prevent the spread of infection. Japan United Kingdom USA Through this, during the COVID-19 pandemic, Korean society provided some degree of health governance for the socially vulnerable classes, such as children, the elderly, and the disabled. However, it is observed that Korean society has neglected to provide welfare governance for the socially vulnerable. In particular, considering the results of this study that the income level of the socially vulnerable has an impact on the mortality rate, it is judged that more income support governance was needed for them. 4.6 Discussion In applying the SVI as an indicator to evaluate a country’s governance, this study assessed how well G20 countries–particularly, South Korea, Japan, the United States, and the United Kingdom–have dealt with the socially disadvantaged during the COVID-19 pandemic. Throughout this paper, I analyzed and drew a connection between COVID-19-related mortality rates and 15 social factors that are used to measure the SVI [Note: As mentioned above, these factors are grouped into four themes: socioeconomic status, household composition & disability, minority status & language, and housing type & transportation]. Based on the results, I will address whether the hypotheses presented in this study were or were not supported. They showed that by ensuring a level of income stability is one of the solutions that prevent excess deaths caused by social vulnerability to the pandemic, thereby supporting the first hypothesis. On the other hand, I found that minority groups, including people from foreign countries, did not have a greater mortality rate relative to the control which did not support the third hypothesis. The data reject the second hypothesis, which puts forth the idea that worse household compositions and presence of disability led to increased COVID-19-related mortality. This could be interpreted as G20 countries’ different perspectives on age groups; specifically, neither the elderly nor the young are considered ‘highly’ socially vulnerable, and that does not affect their mortality rate. Lastly, I did not find that the worse the housing type and transportation, the higher the COVID-19-related mortality; therefore, I reject the fourth hypothesis. In other words, this theme of the SVI cannot be said to be a main issue for G20 countries during the ongoing health crisis. In conclusion, the hypothesis test solely supports the first one, “The worse the socioeconomic status, the higher the COVID-19-related mortality,” among the four hypotheses. This is to say that, depending on how many individuals in a country are positioned in lower social standing, the country may become overwhelmed without the ability to provide care for them, increasing the deaths by COVID-19. Furthermore, the results of this study provides evidence that the research questions hypothesized have been addressed. Regarding the first research question, “How has public-health governance been implemented in the four countries, South Korea, Japan, the United States, and the United Kingdom, during the COVID-19 pandemic?”, I found that these four countries are evaluated to have replaced health governance relatively promptly and smoothly to cope with the global disaster, compared to other countries. In order to prevent the spread of the virus, the four countries have sought a cooperation of citizens, including a group of socially disadvantaged populations, and some implemented measures, such as social distancing, wearing masks, and encouraging citizens to receive vaccinations. The purpose of the second research question is to determine if welfare governance was successfully administered in the four countries, addressing the needs of the socially disadvantaged during these challenging times. Through the analysis of the existing literature, it was observed that welfare governance systems between the countries varied significantly. As an example, I observed the differences between the United States’ (US) and the United Kingdom’s (UK) social safety net implementations. In the UK, social safety net successfully provides for the socially vulnerable class while operating efficiently. Meanwhile, the United States’ social safety net was shown to be inadequate, resulting in a significant number of deaths. South Korea and Japan cooperated to establish a joint welfare governance. The last research question examines the ideal public health governance and welfare governance in the post-COVID-19 phase.The COVID-19 pandemic has caused profound disruptions to the lives of people worldwide (Bonaccorsi et al., 2020; Buckee et al., 2021) and disproportionately affected disadvantaged and underprivileged subpopulations (UN, 2020; Buckee et al., 2021). The devastating social and economic effects caused by COVID-19 necessitate an investigation into the drivers of disease transmission in the past to formulate appropriate and effective preventive strategies in the future. As the major routes of transmission for COVID-19 are reported to be via direct physical contact, aerosols, or droplets, the human movement has been considered critical for the spatial and temporal spread of the disease (Kraemer et al., 2020; Huang et al., 2021). In other words, mobility directly contributes to the dispersal of infections through social contact. However, different social groups in terms of income, employment status, or age may be vulnerable to the disease due to their mobility abilities and patterns, behaviors and lifestyles, and socioeconomic resources. Thus, the interplay between social vulnerability, mobility, and transmission is complex, and there is an urgent need to understand their interrelationships to make more pertinent public health and social measures against future waves of COVID-19 and other public health crises. Gozzi et al. (2021) found it inappropriate and insufficient to apply a uniform relationship between mobility and transmission across counties and social groups with disparate socioeconomic statuses when formulating preventive measures. Understanding such heterogeneous effects can help policymakers target specific social groups and thus make more effective interventions to mitigate COVID-19 transmission and ameliorate social inequity. Moreover, Cutter (2003) showed that social vulnerability is a multiple-dimensional concept rooted in the interactions among social, natural, and engineered systems. With this complexity, social vulnerability is typically conceptualized as consisting of different dimensions; in practice, these dimensions are collapsed into composite indicators such as the Social Vulnerability Index (SoVI) (Spielman et al., 2020). Social vulnerability refers to the potential negative effects on communities that are caused by external stresses on human health. Such stresses include disease outbreaks as well as natural or human-caused disasters. Reducing social vulnerability can decrease both human suffering and economic loss. According to Mah & Andrew(2022) suggested a static Socio-Ecological COVID-19 Vulnerability Index (SEVI) using routinely collected and publicly available data for 6790 small census geographic areas in England. After testing individual items for association with cumulative COVID-19 case rates, the final SEVI is composed of 18 items across four domains (socioeconomic, ecological, health services and epidemiological) which demonstrated statistically significant associations with COVID-19 case rates in multivariable models. Mah & Andrew (2022) show how the SEVI can be used in real time by doing time-stratified analyses, dividing COVID-19 cases into segments before, during and after each national lockdown. With the exception of the time period before the first national lockdown, during which testing was limited and may not have reflected actual disease incidence, the SEVI was predictive in all time segments, with stronger associations outside of lockdown periods. These weaker associations during lockdowns may be due to behaviour change from the policy measures themselves, but could also reflect the inequitable impact of restrictive measures across diverse community settings and are a reminder of the importance of using policy interventions in a way that do not perpetuate vulnerability. For instance, people in vulnerable communities tend to disproportionately work in sectors with no work-at-home option, and as the authors point out, people with precarious employment may face barriers to testing due to fear of losing their jobs. As such, despite the predictive power of this community-level composite index, we should remember that there are still individual-level contributors to social vulnerability that are not captured in the SEVI (SVI and EVI were combined to generate SEVI to explore the overall resilience and risk of developing severe COVID-19). Thus, social vulnerability is associated with the number of confirmed COVID-19 cases and deaths (Karaye & Horney, 2020). SEVIs are pragmatic, harness available data, and can be a powerful tool for local and regional jurisdictions to optimize resource allocation. Flanagan et al.(2011) suggest that SVI is made up of the following elements: socioeconomic, housing composition, minority status and language, and accessibility to housing and transportation. Nayak et al. (2020) examined the association of Social Vulnerability Index (SVI), a percentile-based measure of county-level( participants U.S. counties with at least 50 confirmed COVID-19 cases ) social vulnerability to disasters, and its sub-components (socioeconomic status, household composition, minority status, and housing type/transportation accessibility) with the case fatality rate (CFR) and incidence of COVID-19. Accroding to the results, social vulnerability is associated with higher COVID-19 case fatality. High social vulnerability and CFR coexist in more than 1 in 4 U.S. counties. Kim (2020) examined the spatial distribution of social vulnerability to COVID-19 and its relationship with the number of confirmed COVID-19 cases in 2020, focusing on the Capital region of South Korea. Confirmed COVID-19 cases were concentrated in a specific area of the Capital region. The traditional SVI was more vulnerable in the outer regions of the Capital region, and some central, western, and eastern areas reflected an increase in vulnerability. Healthy SVI was more vulnerable in the northern part of the Capital region, and increase in vulnerability showed in some central areas above Seoul. The results of this study showed that the confirmed COVID-19 cases are associated with increased traditional SVI vulnerability between 2015 and 2019 and have a high positive relationship with the spread of COVID-19. 5. Conclusion This study was conducted to review what governance was like for the socially vulnerable during the COVID-19 pandemic and what could be improved. Thus, this study first analyzed governance levels and COVID-19-related mortality rates for the socially underprivileged in G20 member countries using SVI. Through this, I confirmed that the income support plan reduces COVID-19 related mortality. In other words, it suggests that income support for the socially vulnerable can be the basis of welfare governance and health governance. This study has limitations in that the researcher arbitrarily evaluated the sub-factors of the SVI using the Likert 5-point scale when creating the SVI of G20 countries, and the reliability and validity of the measurement tool were not sufficiently secured. Nevertheless, this study has significance in that it empirically analyzed what kind of governance was needed during the COVID-19 pandemic. References Bonaccorsi G, Pierri F, Cinelli M, Flori A, Galeazzi A, Porcelli F, Schmidt AL, Valensise CM, Scala A, Quattrociocchi W (2020) Economic and social consequences of human mobility restrictions under COVID-19. Proc Natl Acad Sci USA 117(27):15530–15535 Buckee CO, Balsari S, Chan J, Crosas M, Dominici F, Gasser U, Grad YH, B. Grenfell, Halloran ME, Kraemer MU (2020) Aggregated mobility data could help fight COVID-19. Science 368(6487):145–146 Buckee C, Noor A, Sattenspiel L (2021) Thinking clearly about social aspects of infectious disease transmission. Nature 595(7866):205–213 Cutter SL (2003) The vulnerability of science and the science of vulnerability. Ann Assoc Am Geogr 93(1):1–12 Flanagan BE, Gregory EW, Hallisey EJ, Heitgerd JL, Lewis B. A social vulnerability index for disaster management. J Homeland Sec Emerg Manag. 2011;8:1–22. Gozzi N, Tizzoni M, Chinazzi M, Ferres L, Vespignani A, Perra N (2021) Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile. Nat Commun 12(1):1–9 Mah, J. C., & Andrew, M. K. (2022). Social vulnerability indices: A pragmatic tool for COVID-19 policy and beyond. The Lancet Regional Health–Europe, 14. Nayak, A., Islam, S. J., Mehta, A., Ko, Y. A., Patel, S. A., Goyal, A., … & Quyyumi, A. A. (2020). Impact of social vulnerability on COVID-19 incidence and outcomes in the United States. MedRxiv. Karaye IM, Horney JA. The impact of social vulnerability on COVID-19 in the U.S.: an analysis of spatially varying relationships. Am J Prev Med. 2020;59:317–25. Kim, D. (2022). Exploring spatial distribution of social vulnerability and its relationship with the Coronavirus disease 2019: the Capital region of South Korea. BMC public health, 22(1), 1-17. Kraemer MU, Yang C-H, Gutierrez B, Wu C-H, Klein B, Pigott DM, O. C.-D. W. Group, Du Plessis L, Faria NR, Li R (2020). The effect of human mobility and control measures on the COVID-19 epidemic in China. Science 368(6490):493–497 Spielman SE, Tuccillo J, Folch DC, Schweikert A, Davies R, Wood N, Tate E (2020) Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index. Nat Hazards 100(1):417–436 United Nations (UN) (2020). UN Secretary-General’s policy brief: The impact of COVID-19 on women. Available at https://www.unwomen.org/en/digital-library/publications/2020/04/policy-brief-the-impact-of-covid-19-on-women Appendix S1 S2 S3 S4 H1 H2 H3 H4 M1 M2 HT1 HT2 HT3 HT4 HT5 Death SM Argentina 204.49 Australia 149.09 Austria 287.73 Belgium 17.87 Brazil 190.64 Bulgaria 118.77 Canada 74.1 China 2.34 Cyprus 3.15 Czech Republic 424.21 Denmark 75.31 Estonia 65.22 Finland 211 France 6.59 Germany 13.75 Greece 423.35 Hungary 163.37 Iceland 7.54 India 111.6 Indonesia 500.36 Ireland 58.59 Italy 63.06 Japan 137.7 Korea, South 10.57 Latvia 60.18 Lithuania 5.81 Luxembourg 93.68 Malta 113.6 Mexico 29.1 Netherlands 35.8 Poland 275.44 Portugal 660.13 Romania 312.79 Russian Federation 250.9 Saudi Arabia 14.79 Slovakia 173.89 Slovenia 1.58 South Africa 334.55 Spain 23.44 Sweden 78.49 Turkey 11.35 UK 7.94 USA 271.08 1 Mah, J. C., & Andrew, M. K. (2022). Social vulnerability indices: A pragmatic tool for COVID-19 policy and beyond. The Lancet Regional Health–Europe, 14. 2 Cutter, S. L., & Finch, C. (2008). Temporal and spatial changes in social vulnerability to natural hazards. Proceedings of the national academy of sciences, 105(7), 2301-2306. 3 Flanagan, B. E., Gregory, E. W., Hallisey, E. J., Heitgerd, J. L., & Lewis, B. (2011). A social vulnerability index for disaster management. Journal of homeland security and emergency management, 8(1). 4The G20 is a gathering of 20 countries and regions, including the G7 leading the global economy, plus 12 emerging countries, major economies, and the European Union (EU). In particular, the absence of an international crisis replacement system related to finance and foreign exchange was pointed out as a problem after the Asian financial crisis. Accordingly, at the annual meeting of the IMF held in September 1999, the establishment of the G20, in which the G8 countries and major emerging market countries participated, was proposed. In December 1999, the G20 Finance Ministers’ Meeting was held for the first time in Berlin, Germany, where finance ministers and central bank governors from major developed and emerging countries gathered together to widely discuss major economic and financial issues of the international community. As the need for cooperation between developed and emerging countries emerged to overcome the crisis caused by the global financial crisis, the G20 Summit was upgraded to a summit meeting and was held in Washington, D.C., USA, for the first time in 2008. 5 The related URLs are as follows.https://worldpopulationreview.com/country-rankings/poverty-rate-by-country https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_2KAA335 https://datatopics.worldbank.org/world-development-indicators/the-world-by-income-and-region.html https://www.worlddata.info/average-income.php https://data.worldbank.org/indicator/SE.SEC.CUAT.UP.ZS?end=2021&start=1970 https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS https://unstats.un.org/unsd/demographic-social/sconcerns/disability/statistics/activities#!/countries https://repositorio.cepal.org/bitstream/handle/11362/5040/2/S2011011_en.pdf https://www.researchgate.net/figure/Disability-incidence-in-six-West-African-countries_tbl1_235347433 https://www.disabilitydataportal.com/explore-by-country/djibouti/1/ https://www.pewresearch.org/religion/2019/12/12/religion-and-living-arrangements-around-the-world/ https://worldpopulationreview.com/country-rankings/immigration-by-country https://www.ef.com/wwen/epi/ http://chartsbin.com/view/42112 https://en.wikipedia.org/wiki/List_of_countries_by_vehicles_per_capita https://ec.europa.eu/eurostat/web/products-eurostat-news/-/ddn-20210521-1 https://www.oecd.org/social/family/HM1-5-Housing-stock-by-dwelling-type.pdf https://en.wikipedia.org/wiki/List_of_countries_by_number_of_households#cite_ref-auto_2-7 6 North Korea officially announced that there have been no COVID-19-related deaths from 2020 to now, and China also distorted the facts and reported them to international organizations as if there were no recent COVID-19 deaths. 7 Heryadi, M. D., & Hartono, D. (2017). Energy efficiency, utilization of renewable energies, and carbon dioxide emission: case study of G20 countries. International Energy Journal, 16(4). 8 Humphreys, L. G., & Park, R. K. (1981). Analysis of variances and covariances is misleading as a guide to a common factor model. Intelligence, 5(2), 157-163. 9 Hintze, J. L., & Nelson, R. D. (1998). Violin plots: a box plot-density trace synergism. The American Statistician, 52(2), 181-184.
Can you help me write my thesis paper? Can you write me… 1. analysis part 800-900 words 2. abstract/introduction 500 words based on the draft of my paper? I will explain them in detail after I hir
Lee 23 Name (student ID#:) Advanced Seminar E-1 ILA Spring 2022 Governance of Disaster-Vulnerable Classes in the COVID-19 Pandemic: A Comparative Analysis of Public-Health and Welfare Governance Policy Abstract As the COVID-19 pandemic continues, a new role of governance has been established. This study reveals how several countries’ different forms of governance affected their responses to the pandemic, particularly for the socially disadvantaged, who are also known as “disaster-vulnerable classes.” Countries with a democratic system of governance guaranteed citizens some extent of freedom. Meanwhile, authoritarian governance, like that of China, was intimately involved in every aspect of people’s lives in order to control the spread of the virus. As a result, the lives of the disaster-vulnerable classes in each country turned out differently. This study aims to examine the welfare governance for socially vulnerable groups during the COVID-19 pandemic. By using a method of comparative analysis, this study compares patterns of governance for each country for the disaster-vulnerable groups, represented by children, the elderly, and the disabled. Accordingly, this study proposes that countries establish systems of global health governance to more effectively manage those in need during the worldwide chaos caused by the novel virus. It also shows that system resilience is needed instead of a simple crisis-management approach. Introduction As the COVID-19 pandemic has become a worldwide pandemic and changed people’s daily lives, it has challenged countries’ governance. The concept of “governance” has emerged in a society where the government’s administrative failures are repeated while globalization continues to grow. As a result, contemporary governance has become increasingly complicated, both in terms of the goals being pursued and the instruments being used to pursue those goals (Peters, 2011). Among many forms of governance, this study focuses on public-health governance and welfare governance. Many countries have struggled with choosing an appropriate strategy to mitigate the COVID-19 pandemic. This includes a soft-passive approach based on herd immunity and a hard-forceful approach, such as lockdowns and physical distancing (Moon, 2020). In summary, this present paper examines the effects of ‘participatory’ public-health governance and ‘controlled’ public-health governance through literature research. Governance acts as a control tower during national disasters, such as pandemics, typhoons, and earthquakes (Wang et al., 2021). There is a group of people named “disaster-vulnerable groups” who are vulnerable to the crisis caused by the above-mentioned disasters. They include the disabled, children, and the elderly. In this regard, it will be a meaningful study to examine the role of welfare governance for disaster-vulnerable groups in the face of the COVID-19 pandemic since few studies have been conducted on related topics. To summarize, this study will examine the role of governance, especially in public-health and welfare governance for disaster-vulnerable groups during the ongoing health crisis. To show how the existing studies have shaped my proposed study, this present paper will first clarify the definition of “governance” and how countries have differently accepted governance policies and procedures. Then, this paper will discuss public-health governance, dividing it into a hard-forceful strategy and a short-passive strategy, and how each has affected society, as well as people’s lives. This paper will also briefly describe the disaster-vulnerable groups and how welfare governance in a couple of countries has treated them. Finally, this paper will conclude with the plans for further research to find the desirable public-health and welfare governance. Literature Review There are various types of governance related to COVID-19. However, this study focuses on the literature regarding the two governances–public-health governance and welfare governance–for disaster-vulnerable classes, which include children, the elderly, and the disabled. Overview of Governance It is necessary to clarify the definition of “governance” used in this study. Since there is no academic consensus on the definition of “governance,” scholars have employed many different interpretations of the term in accordance with the distinct contexts of their respective studies. In other words, governance can be either flexible and easily adapt to many different topics or ambiguous and unclear (Vymetal, 2007; Kaufmann & Kraay, 2007). This study focuses on the definition by Hyden and Court (2002) that “governance” refers to “the exercise of economic, political, and administrative authority to manage a country’s affairs at all levels.” This is to say that, governance not only includes the central government but also practices and institutions organized by citizens who politically contribute to the country. As globalization spread throughout the twentieth century, global governance appeared in response to the raising concerns about the increased number and influence of non-state actors. This eventually led to a shift in which non-state actors came to participate in countries’ decision-making and thus greatly affect modern-day international relations. For example, global issues were often considered to be dissolved via intergovernmental cooperation, whereas in the contemporary era, international organizations have progressively become involved in helping countries deal with those issues (Weiss, 2000). In conclusion, “governance” can be defined as the process of problem-solving in the interaction between state and non-state actors. More recent studies have highlighted the importance of the term “good governance” (Weiss, 2000; Webster, 2008; Singh et al., 2009). Although there is no widely accepted definition of the term, its crucial elements encompass “accountability” (Adejuwon, 2012). Sirghani et al. (2013) add that the private sector, civil society organizations, and governmental institutions must be accountable to the public. By consistently moving toward a vision and ensuring that daily operations are in line with organizations’ objectives, good governance builds a solid future for itself. According to Vanlahlimpuii (2018), good governance is intrinsically related to leadership. She demonstrated the qualities of effective leadership that are required to achieve good governance. These include, “the ability to be responsive, effective and efficient, inclusive and build consensus, set strategic vision […] delivering trust and values” (Vanlahlimpuii, 2018). Such leadership enables the building of good governance that boosts a company’s financial and social outcomes and ensures that the resources provided by the owners are used wisely (Deloitte Netherlands, 2016). Meanwhile, poor governance can put companies at risk for economic failure, financial difficulties for directors and trustees, and legal issues. It can also cause an organization to lose focus on its mission and its obligations to its owners and other stakeholders who stand to gain from its success (Peters & Pierre, 2010). In countries with liberal democratic systems such as those of Western Europe, North America, Korea, and Japan, the implementation of top-down administrative power through strong governance has disappeared. They have been replaced by an “organized society,” which plays an important role in providing numerous crucial services through collaborative initiatives. In essence, these programs are “interconnected clusters of businesses, organizations, and governments that join together inside the framework of these programs” (Hjern & Porter, 1981). These implementation structures operate within the parameters of a governance concept that has drawn a surprisingly high level of consensus. According to a widespread perspective that embraces governance as a subject far larger than “government,” the governance approach is considered a “new process of governing, or a changed state of the ordered rule, or the new means by which society is ruled” (Stoker, 1998). However, communist countries such as China, as well as countries with totalitarian political systems, are exceptions. This study defines “governance” as a problem-solving process, which is conducted via the interactions of different segments of society. These segments include the government, civic groups, and corporations, in lieu of simple management or administration. Specifically, this paper examines public-health governance in response to the COVID-19 pandemic and welfare governance for the elderly, children, and the disabled, who belong to the disaster-vulnerable group. Public-Health Governance According to the literature-based evidence, the COVID-19 pandemic put governance, as well as social-economic systems, around the world at risk. The crisis revealed social inequalities and widened the gap that existed in society before the pandemic, which is why countries’ public health governance should be examined. Even though there are numerous definitions, the term “public-health governance” can be interpreted as “the ways in which different public, non-governmental, or private actors work together to support communities in preventing disease and achieving health, wellbeing, and health equity” (Ruggiero et al., 2022). Additionally, Carlson et al. (2015) enumerated six functions of public-health governance: developing policies and strategies, managing resources, legislating, engaging partners and communities, facilitating continuous improvement, and overseeing a public health department. This study classifies countries’ public-health governance in two ways depending on their responses to the pandemic–hard-forceful and soft-passive strategies–and briefly discusses their outcomes of them. A Hard-Forceful Strategy. A typical policy for a hard-forceful strategy is a lockdown, which can be divided into household and industrial lockdowns. Home quarantine, as well as physical distancing, are measures to encourage people to stay at home as much as possible, maintain distance from each other in public places, and wear masks. These can be “voluntary” (motivated by personal fears of infection and/or social norms) or “mandatory” (exercised by the government) (Shojaei & Salari, 2021). On the other hand, industrial lockdown measures to serve to substantially reduce contact among employees in non-essential, contact-intensive businesses. Many governments around the world have mandated these policies; however, they can also be voluntary, with firms shutting down operations because their labor force can be infected or their customers can avoid contact-intensive venues (Robinson et al., 2021). China and North Korea have shown the strongest enforcement of those lockdown policies. These two countries share common attitudes toward the pandemic, enforcing “zero COVID-19” and operating political systems of centralized socialist states (Chen & Chen, 2022). Nevertheless, their policies may result in human rights violations, and thus their effectiveness is still questioned. North Korea has a low trade volume and is well-known as “the worst human rights country,” which is why it persists in these policies (Burghart et al., 2020; Cheong, 2003). Meanwhile, it would be difficult for China, one of the world’s major economic powers, to continue its zero COVID-19 policy, which necessitates a lockdown policy. As mentioned above, the concept of lockdown as an international reaction to the pandemic is questionable. Ren (2020) raised questions about the effectiveness of lockdown policies through a study on the impacts of the COVID-19 pandemic and lockdown. He found that the lockdown policy caused the following problems. First, it is costly to start; for instance, the lockdown has caused business closures and soaring unemployment rates. Second, it also makes inequity worse. Diverse socioeconomic classes have pretty different levels of access to working from home. The poor are less able to do so, and many sink further into poverty, whereas the middle class can use home-based strategies to work. Third, from the standpoint of controlling infectious diseases, it is not the best strategy to stop transmission. This paper examines whether it is wrong to implement a lockdown policy to control highly contagious diseases such as the COVID-19 pandemic. Ren’s (2020) article sheds light on the fact that the lockdown policy did not contain the spread of COVID-19, nor did it revitalize the local economy, and there was no consideration for vulnerable groups. This study believes that the aspects of welfare governance for disaster vulnerable groups may differ in countries where public-health governance is implemented based on this strategy. Therefore, this study will describe welfare governance during the COVID-19 pandemic in the next section. A Soft-Passive Strategy. A soft-passive strategy, which relies on community immunity or herd immunity, was tested in several countries as a part of their pandemic response efforts (Uddin, 2021). Governments with a soft-passive approach initially carried out a partial lockdown policy. Nevertheless, most of them concluded that they could not control the spread of the virus with a hard-forceful strategy like lockdown. While the relationship between culture and the effectiveness of government has been researched, Moon’s (2020) study shows that lots of Western democratic countries put a great amount of their budget to foster “their open and free society.” This implies that, in these countries, tactics, such as China’s strict lockdown policy, are unlikely to be readily adopted. As some European nations failed to successfully mitigate the situation at first, they slowly moved from a soft-passive strategy to a hard-forceful one by implementing the following policies: stepping up their testing capacity, enforcing quarantines, and enforcing partial lockdowns while placing a greater emphasis on citizen cooperation (Moon, 2020). However, Western governance invites various sectors of society to engage in government activities, which is known as a “bottom-up governmental system” (Saito, 2008). Therefore, even if governance that does not apply coercive methods such as lockdown is inefficient, it can induce more members of society to participate voluntarily. To reduce the number of positive cases and be ready for the issues followed by socio-economic recovery in the upcoming future, governments require to analyze the failures of their responses that have already occurred and strengthen their governance capabilities accordingly. Governance that adopts this loosely formed strategy must create cooperative tactics that involve not only government but also civil society, academia, and other groups to ensure citizen participation. It should be communicated clearly, and it can be said that cooperation and smooth communication between each organization is required. To overcome the COVID-19 crisis through participation, Nordic Western countries and the United States adopted a “with Covid” strategy (Emanuel et al., 2022) rather than adopting a zero COVID-19 policy or unilateral lockdown policy like China did. The present paper also favors a soft-passive approach emphasizing citizen participation and autonomy rather than China’s unilateral lockdown method. In particular, the South Korean government invented the “agile‐adaptive approach” (Moon, 2020). South Korea was enabled to track down confirmed patients’ contact and further identify potential COVID-19 cases in a short time period, contributing to the nation’s advanced information. The approach of the South Korean government is analyzed in detail later. Welfare Governance The COVID-19 pandemic has affected people’s welfare, including disaster-vulnerable groups. This study will deal with welfare governance, concerning food security, education, and health in major countries during the crisis. In this regard, this present paper shows an overview of disaster-vulnerable groups and welfare governance for them in turn. Disaster-Vulnerable Group. This present paper examines welfare governance for disaster-vulnerable groups. Disaster-vulnerable groups can disproportionately include certain categories due to certain vulnerabilities and the impact of social, economic, and cultural systems. These categories may vary by country and region, but they generally encompass women, low-income groups, the elderly, migrants, children, and persons with disabilities (UNDP, 2015). Disaster-vulnerable groups can be classified in terms of physical, environmental, and economic aspects. First of all, in the case of the physically vulnerable, those who lack the ability to evacuate and respond independently in the event of a disaster are the disabled, the elderly, and children (Marshall et al., 2020). The elderly can be classified as those who are over the age of 65 and whose activities have begun to decline; the disabled people are those with physical disabilities, and children refer to those under the age of 13 (who have weak judgments in various situations). Governance for Disaster-Vulnerable Groups. Norway’s response to COVID-19 is considered successful, but the government’s response to disaster-vulnerable groups, such as children and the elderly, is regarded as insufficient (Christensen, 2021; Christensen & Laegreid, 2020). For the youth, financial assistance and job security could affect their lives to a great extent since they positively affected their families. Nevertheless, the government barely dealt with the reduced interactions with others (isolation) and the support given by the school and other organizations. The elderly relatively received more attention than children. The policy toward this group also is considered a ‘failure’ in two ways: “a lot of the elderly in nursing homes died, and they suffered from social isolation due to the paternalistic attitude on the part of the government” (Christensen, 2021). In fact, many governments have had to cope with at least three issues at once. First, it is their responsibility to protect the public’s health, actively preventing the spread of COVID-19 and offering better healthcare. Second, each government needs to consider the virus’s economic impact because it seemed to be almost ignored in its policy as the economic aspect should be ‘sacrificed’ to protect more citizens’ lives (Baldwin & Weber di Mauro, 2020). Third, the social and psychological impact needs to be considered, which has received much less attention from policymakers than the other issues caused by the pandemic (Christensen, 2021). Lu et al. (2020) reported that, in China, the management of nursing homes inhabited by disaster-vulnerable groups was strengthened during the COVID-19 pandemic. Welfare organizations, that provide homes for the elderly, children, and people with disabilities, are regarded as “higher-risk areas.” This is because of their poor environment caused by “high-density living spaces and collective actions,” which has made them more vulnerable. However, their studies reported that there was a shortage of caregivers to work in nursing homes where disaster-vulnerable groups resided during the COVID-19 pandemic. Depending on the form of government, governance can take many forms, clearly distinguished from the response to disaster-vulnerable groups in crisis. In short, the present paper examines whether, and to what extent, major countries have provided public health and welfare governance for disaster-vulnerable groups during the COVID-19 crisis. Methodology This study aims to examine how public-health governance and welfare governance for the disaster governance for the disaster-vulnerable class are implemented in the COVID-19 pandemic. Thus, this study presents the following research questions (hereafter RQ): How has public-health governance been implemented in the four countries, South Korea, Japan, the United Kingdom, and China, during the COVID-19 pandemic? (RQ 1); How has welfare governance for disaster-vulnerable groups in the four countries changed throughout the pandemic? (RQ 2); What is the desired direction for public health governance and welfare governance in the post-COVID era? (RQ 3). In responding to the above research questions, a comparative study is suitable because, as Yoo et al. (2020) state, it enables the researcher to “examine how the differences in institutional contexts and governance structures shaped policy responses and policy outcomes.” This would help scholars comprehend the relationship between types of governance and how countries manage the situation. This would also involve comparative strategies, such as Mill’s Method of Agreement (MoA) and Method of Difference (MoD), to efficiently compare countries and find the best practice. Since the MoA and MoD respectively show the similarities and differences between several instances, they will be helpful in this study, which discusses how South Korea, Japan, the United Kingdom, and China treated the disaster-vulnerable class and have implemented public-health governance during the COVID-19 pandemic (Heuveln, 2000). This study explores how the above-mentioned countries worked for the socially disadvantaged during the COVID-19 era by assessing whether each governance effectively helped those in need. Specifically, this study compares different instances of democratic governance and further compares democratic governance versus autocratic governance as a whole. The former includes South Korea, Japan, and the United Kingdom, which employed soft-passive strategies. By using the MoA, the study reveals similarities between democratic governance in terms of the treatment of the socially disadvantaged during the pandemic as well as the perception toward the group. Meanwhile, this study also uses the MoD to show the characteristic of each country’s unique governance and aims to identify the effective one. By contrast, the latter group only encompasses China, which tightened its autocratic governance structure and facilitated hard-forceful strategies during the pandemic (Ramay & Babur, 2020). Applying the MoD, this study compares China and countries with democratic governance, showing differences between how different types of governance affect the management of the socially disadvantaged. Through this comparison, this study concludes what desirable public-health and welfare governance are for disaster-vulnerable groups during a health crisis. Summary This study explores the role of governance, particularly public-health and welfare governance for disaster-vulnerable groups during the COVID-19 pandemic. The existing literature reveals that public-health governance with either a hard-forceful or a soft-passive strategy toward the health crisis led to different outcomes. Specifically, the former failed to protect public health, including disaster-vulnerable citizens, and deal with the impacts of the pandemic, whereas the latter successfully encouraged members of society to willingly cope with the issue. The reviewed literature review also suggests that countries’ own welfare governance largely affected the treatment of their disaster-vulnerable citizens during the pandemic; however, in found cases, most of their welfare governance malfunctioned to take care of them. By using comparative methods, further study will focus on comparing public-health and welfare governance of the four countries, South Korea, Japan, the United Kingdom, and China, for the disaster-vulnerable community. This will help find the most appropriate one to cope with the health crisis. References Adejuwon, D. (2012). The Dilemma of Accountability and Good Governance for Improved Public Service Delivery in Nigeria. Africa’s Public Service Delivery & Performance Review, 1(3), pp. 25-45. Baldwin, R., & Weber di Mauro, B. (2020). Economics in the Time of COVID-19. Centre for Economic Policy Research (CEPR) Press. Burghart, S., Park, D., & Zakharova, L. (2020). The DPRK’s Economic Exchanges with Russia and the EU Since 2000: an Analysis of Institutional Effects and the Case of the Russian Far East. Asia Europe Journal. 18, pp. 281-303. Carlson, V., Chilton, M., Corso, L., & Beitsch, L. (2015). Defining the Functions of Public Health Governance. American Journal of Public Health. 105(S2), S159-166. Chen, M., & Chen, Q. (2022). China Can Prepare to End its Zero-COVID Policy. Nature Medicine. 28(6), pp. 1104-1105. Cheong, W. (2003). Protection of North Korean Human Rights and Simultaneous Improvements for Peace on the Korean Peninsula. In National Human Rights Commission of the Republic of Korea (Eds.), North Korean Human rights: Trends and Issues (pp. 41-53). National Human Rights Commission of the Republic of Korea. Christensen, T. (2021). The Social Policy Response to COVID-19 – The Failure to Help Vulnerable Children and Elderly People. Public Organization Review. 21(4), pp. 707-722. Christensen, T., & Lægreid, P. (2020). Balancing Governance Capacity and Legitimacy: How the Norwegian Government Handled the COVID-19 Crisis as a High Performer. Public Administration Review. 80(5), pp. 774-449. Deloitte Netherlands. (2016). Good Governance Driving Corporate Performance?: A Meta-Analysis of Academic Research & Invitation to Engage in the Dialogue. Nyenrode Business Universiteit. Emanuel, J., Osterholm, H., & Gounder, R. (2022). A National Strategy for the “New Normal” of Life with COVID. Jama. 327(3), pp. 211-212. Heuveln, B. (2000). A Preferred Treatment of Mill’s Methods: Some Misinterpretations by Modern Textbooks. Informal Logic. 20(1), pp.19-42. Hjern, B., & Porter, D. (1981). Implementation Structures: A New Unit of Administrative Analysis. Organization Studies. 2(3), 211-227. Hyden, G., & Court, J. (2002). Governance and Development. World Governance Survey Discussion Paper 1. Kaufmann, D. & Kraay, A. (2007). Governance Indicators: Where are We, Where Should We be Going? Policy Research Working Paper. 4370. Lu, Q., Cai, Z., Chen, B., & Liu, T. (2020). Social Policy Responses to the COVID-19 Crisis in China in 2020. International Journal of Environmental Research and Public Health. 17(16). Marshall, J., Wiltshire, J., Delva, J., Bello, T., & Masys, J. (2020). Natural and Manmade Disasters: Vulnerable Populations. In A. Masys, R. Izurieta, M. Reina Ortiz (Eds.), Global Health Security: Recognizing Vulnerabilities, Creating Opportunities (pp. 143-161). Springer. Moon, J. (2020). Fighting COVID-19 with Agility, Transparency, and Participation: Wicked Policy Problems and New Governance Challenges. Public Administration Review. 80(4), pp. 651-656. Peters, B. (2011). Steering, Rowing, Drifting, or Sinking? Changing Patterns of Governance. Urban Research & Practice. 4(1), pp. 5-12. Peters, B., & Pierre, J. (2010). Economic Crisis, Public Administration, and Governance. Korean Journal of Policy Studies. 25(1), pp. 59-71. Ramay, S., & Babur, A. (2020). Characteristics of Chinese Governance Model. In S. Ramay & A. Babur (Eds.), Governance and Development Model of China (pp. 2-9). Sustainable Development Policy Institute. Ren, X. (2020). Pandemic and Lockdown: A Territorial Approach to COVID-19 in China, Italy, and the United States. Eurasian Geography and Economics. 61(4-5), pp. 423-434. Robinson, S., Levy, S., Hernandez, V., Davies, R., Gabriel, S., Arndt, C., Seventer, D., & Pleitez, M. (2021). COVID-19 and Lockdown Policies: A Structural Simulation Model of a Bottom-Up Recession in Four Countries. Ifpri Discussion Paper. Ruggiero, E., Bhatia, D., Umar, I., Arpin, E., Champagne, C., Clavier, C., Denis, J., & Hunter, D. (2022). Governing for the Public’s Health: Governance Options for a Strengthened and Renewed Public Health System in Canada. National Collaborating Centres for Public Health. Saito, F. (2008). Decentralization and Local Governance: Introduction and Overview. In Foundations for Local Governance. In F. Saito (Eds.), Foundations for Local Governance: Decentralization in Comparative Perspective (pp. 1-24). Physica-Verlag. Shojaei, A., & Salari, P. (2021). COVID-19 and the “Stay at Home” Recommendation: An Ethnographic Study. Journal of Education and Health Promotion. 10(62). Singh, D., Ansari, N., & Singh, S. (2009). Good Governance & Implementation in Era of Globalization. The Indian Journal of Political Science. 70(4), pp. 1109-1120. Stoker, G. (1998). Governance as Theory: Five Propositions. International Social Science Journal. 50(155), pp. 17-28. Uddin, F. (2021). COVID-19 Pandemic Is About More Than Health: A State of Governance Challenges in Bangladesh. South Asian Survey. 28(1), pp. 72-91. United Nations Development Programme (UNDP) (2015). Human Development Report: Work for Human Development. United Nations Development Programme. Vanlahlimpuii, J. (2018). Leadership and Good Governance. Mizoram University Journal of Humanities & Social Sciences. 4(2), pp. 61-72. Vymetal, P. (2007). Governance: Defining the Concept (Publication No. MSM6138439909). [Research plan, University of Economics, Prague] Faculty of International Relations Working Papers. Wang, H., Chen, G., Lee, W., You, S., Li, C., Jang, J., & Shieh, C. (2021). Learning From Each Other in the Management of Natural Disaster and COVID-19 Pandemic: A Case Study in Taiwan. Frontiers in Public Health. Webster, N. (2008). Good Governance; Between-Idealism and Realism. Danish Institute for International Studies. Weiss, T. (2000). Governance, Good Governance, and Global Governance: Conceptual and Actual Challenges. Third World Quarterly. 21(5), pp. 795-814. Yoo, J., Dutra, S., Fanfan, D., Sniffen, S., Wang, H., Siddiqui, J., Song, H., Bang, H., Kim, D., Kim, S., & Groer, M. (2020). Comparative Analysis of COVID-19 Guidelines From Six Countries: a Qualitative Study on the US, China, South Korea, the UK, Brazil, and Haiti. BMC Public Health. 20 (1853).