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EH 1020 Columbia Southern University Cybersecurity Research Proposal
I’m working on a nursing multi-part question and need support to help me study.
Purpose of Assignment:Professional nurses must be able to identify relevant practice issues, appraise literature and integrate credible evidence into innovative, evidence-based practice solutions for positive outcomes.Course Competency:Propose an evidence-based solution aligned with an evidence-based practice question.Explain the relationship between research, theory, and evidence-based practice.Instructions:Content:Applying The Iowa Model Revised: Evidence-Based Practice to Promote Excellence in Health Care create a written proposal for these two components of a proposal for an evidence-base practice solution.Identify and describe in detail a practice issue identified in your workplace or clinical experience includingDescription of the relevance of practice issue to organizational prioritiesSupporting internal and external data to support the need for proposed practice changeCreate a research question using the PICO format with a description of each component.P= PopulationI=InterventionC=Comparison InterventionO=OutcomesFormat:Use the Template for the Course ProjectStandard American English (correct grammar, punctuation, etc.)Logical, original and insightfulProfessional organization, style, and mechanics in APA formatSubmit document through
Rasmussen College Evidence Based Questions in Research Problem Essay
A Study of Household Income Consumption Expenditure in India
PART – B Proposed Research Work 9 (i) Project Title: “Inequality in Indian Society: A Study of Household Income Consumption Expenditure” (ii) Introduction With economic and social progression of the nation the minimal basket of basic human needs which a society would expect for its citizen may be expected to keep expanding. These changes in the basic needs of the society may be affordable by the level of income. The level of income of the households ensures the minimum standard of living in the society. Household income and consumption expenditure are two direct monetary measures used in assessing the economic well-being of a population. However, consumption expenditure is preferred to income as it reflects long-term economic status of the household, particularly in low income countries (Friedman 1957). It is important to note however that expenditures are not similar with income, which may even be a better indicator of well-being, for various reasons. Among them is the possibility of consumption without expenditures at least within the same period. According to Atkinson, (1998), “Expenditures are thus supposed to better reflect “long-term” or “permanent” income and are from this point of view considered to be a better measure of economic well-being and respective inequalities”. Besides, in developing countries, income estimates are under-reported, drawn from multiple sources and vary across seasons. Though the consumption expenditure data are collected in many developing countries including India, the process is time-consuming, expensive and needs adjustment for household size, composition and for price level. Owing to these difficulties, the economic proxies (consumer durables, housing quality and household amenities) are collected to measure the economic status of the households in both small-and large-scale population-based surveys. Inter Disciplinary Relevance: In the context of the growth performance during these two decades, economists and policymakers have become interested in the trends in regional inequality during this period. Rising regional inequality can create economic, social and political problems for any country. For the Indian economy, it has serious ramification for the continuation of the reform process. Hence, it is of utmost importance to understand the regional disparity in terms of consumption expenditure on consumer durables, housing quality and household amenities of the economy. Household expenditures as they result from budget limitations at the one hand and choices based on needs, demand, preferences etc. on the other may be regarded as manifestations of economic and social inequalities as well as cultural differences and social distinctions. Studying the patterns, disparities and determinants of household expenditures and their changes across time by making use of large scale population surveys thus seem to be promising in various respects. At a most general level it may provide insights into general consumption behaviour as a major source of human well-being and respective choices and restrictions. Investigating household expenditures and consumption patterns is considered to be key for the monitoring and explanation of inequalities and changes in material living standards and general welfare. Studying expenditures and consumption behaviour of households also seems to be an important and promising strategy to extend and supplement mainstream approaches of studying inequality as a key topic of sociological and economic research. As one would expect, research on household expenditures and consumption is much more common and popular among economists and looks back to a long tradition in economics (Stigler, 1954). This issue was also addressed by Houthakker (1957) as early as in the 1950s. The issues related to household expenditures and consumption have been disregarded in sociology and particularly empirical sociological research to a large degree, although family and household budget data frequently used for empirical study in the early days. Some observers and commentators of developments in sociological research thus conclude that consumption has been strongly neglected in sociological research (Rosenkranz and Schneider, 2000). Thus it is an area which needs greater attention to be paid. Review of Research and Development in the Subject: International status Although there is a long history of research on patterns of household expenditures and their changes across time, which goes back to the 19th century and the famous work by Ernst Engel and others, these questions have attracted surprisingly little attention in recent years. Blacklow and Ray, (2000) in their paper compare, using Australian unit record data, income and expenditure inequalities over the period 1975-76 to 1993-94. The study finds inconsistencies between the two inequality movements over much of this period. They, also, observe differences in the nature of income and consumption disparities. Bögenhold and Fachinger, (2000) used repeated cross sectional data (RCS) in their empirical analysis which is based on the West German Income and Expenditure Survey (IES) in 1973, 1978, 1983, 1988 and 1993. The results revealed that the relationship between income and expenditure is given but it is weak. All in all, the social organisation of consumption is a research object in itself to obtain information about the living standard of individuals and households. Zaidi and Klass (2001) in their study on poverty and inequality in developed countries focus on income. This paper presents trends in consumption-based poverty and inequality in nine member countries of the European Union. During the 1980s, both poverty and inequality increased in Italy, France, the United Kingdom, Germany and Belgium, while decreases in both poverty and inequality are observed for Spain and Portugal. In Greece only inequality increased. Dhawan-Biswal, (2002) measure inequality in Canada with a comprehensive look at inequality trends in Atlantic Canada during the period 1969 to 19966. They use consumption expenditure as a measure of family well being and compare it with the income based measure of well being. Overall consumption inequality has continuously been lower in Atlantic Canada in comparison to the rest of Canada. Meyer and Sullivan, (2003) found in their study that it is fairly compelling that most households can more easily report income. They suggested that use consumption to supplement income in analyses of poverty whenever possible. Kalwij and Salverda, (2004) examine in detail the changes in household expenditures patterns, and in particular services related expenditures, in the Netherlands over the years 1979, 1989 and 1998. Using Engel curve estimations, these changes are related to changes in household demographics, employment, the budget and relative prices. They find that the dominating changes in demand are decreasing shares of expenditures on food and clothing and an increasing share of expenditures on housing. Decrease in food expenditures is for a large part explained by changes in household characteristics and the budget and about a third is a price effect. The increase in housing expenditures share is predominantly a price effect. Blow, Leicester and Oldfield (2004) examined “how and why has the way in which the average British family spends its money changed over the past 25 years” by using data from the UK FES between 1975 and 1999. It looks not only at broad changes in total spending, but also at how the division of expenditure between basics and non-basics and between durable goods, non-durable goods and services has altered over time. Johnson, Smeeding and Torrey (2005) used the period 1981 and 2001, to measure economic inequality among groups in the general population in the United States. Two measures of income and consumption are used to gauge relative well-being. Households with children are at a disadvantage, relative to the general population through both prisms. And households with children are the only group whose distribution of consumption was relatively more unequal than their distribution of disposable income throughout the 1981-2001 period studied. Comparison with the general population is a zero-sum game where households with children are relatively less well off, regardless of whether disposable income or consumption is used as the resource measure. Brewer, Goodman, and Leicester, (2006) in their study on “Household spending in Britain” by using 30 years of data from household surveys conclude that “although there has been much recent emphasis on the advantages of measures of household expenditures in assessing household welfare in more academic circles, this has yet to work its way into the mainstream poverty measurement debate”. This study shows the trends in poverty in Britain since the 1970s when household expenditure is used as a measure of financial well-being, rather than household income and investigates how using spending, rather than income, as a measure of well-being alters our view of who is poor. It examines the spending levels of the lowest-income households and analyses whether low-income pensioners’ spending on basic and non-basic items increased as a result of the large increases in entitlements to means-tested benefits since 1999. Zhang, Xie and Zhou, (2009) studied the disparity of consumption expenditure among rural areas in China by principle and method of cluster analysis. Results showed that income and consumption expenditure of 31 districts, cities and provinces could be divided into 5 classes of income and consumption. Shanghai City was the only city rated as the first-class areas with highest income and consumption. National status Review of literature in India Bhattacharya and Mahalanobis (1967) had decomposed the Gini-coefficient and the standard deviation of logarithms for the year 1957-58 based on the household consumer expenditure survey data of India and found that one-quarter of the total inequality was being explained by between-state inequality and the remaining three-quarters was explained by the within-state inequality. Paul, (1988) studied the importance of household composition in the analysis of inequality measurement based on the National Sample Survey data (25th round). The results for rural Punjab reveal that the ranking of households by per equivalent adult consumption expenditure (PEAE) differs significantly from the ranking by per capita consumption expenditure (PCE). Many households classified as poor according to the criterion of PCE are not so classified by the criterion of PEAE. The exercise also reveals that the distribution of HCE, if not adjusted for household size and composition effects, gives biased measures of the extent of true inequality. Jain and Tendulkar (1989) in their paper deduces the analytical conditions for the movements in the same or in the opposite direction of the real and the nominal relative disparity in cereal consumption consequent upon the differential movements in the prices of cereals faced by the bottom and the top fractile groups of the population. These conditions are used for interpreting the movements in the real and the nominal relative disparity with reference to the Indian rural population over the period from 1953 to 1978. Datt and Ravallion, (1990) argued that the costs and the benefits of regional policies will tend to be borne widely within regions. Some benefits are likely to leak to the nonpoor in recipient regions, and some costs to the poor in donor regions. The paper suggests that the quantitative potential for alleviating national poverty through purely regional redistributive policies is small. Even assuming no political problems, the maximum impact on poverty is nomore than could be achieved simply by giving everyone a uniform (untargeted) windfall gain equal to about 1.5 percent of India’s mean consumption. And other considerations – including increased migration to areas of higher benefits – make it unlikely that the maximum impact will be attained in practice. Greater alleviation of poverty requires supplementary interventions that reach the poor within regions, by reducing the costs borne by the poor in donor regions and enhancing benefits to the poor in recipient regions. Mishra and Parikh (1992) in their paper measured household consumer expenditure inequalities in India by regions (states) and sectors (urban-rural) for the years 1977-78 and 1983 based on the National Sample Survey data. The results consistently indicate that the inequality within states contributes much more towards national inequality and within-sector inequality explains a large part of state level inequality. The inequality at state levels has shown a decline from 1977-78 to 1983 due to a better monsoon season in 1983, and anti-poverty programmes. Dubey and Gangopadhyay (1998) in their analytical report mention intra-state disparities by using NSSO consumption income data set. There are several states in India where the incidence of poverty across regions within a state is very high. They reported for seven regions of Madhya Pradesh, poverty incidence varied from one of the lowest in the country in the western region to one of the highest in the eastern region. Deaton and Dreze (2002) in their paper presents a new set of integrated poverty and inequality estimates for India and Indian states for 1987-88, 1993-94 and 1999-2000. The poverty estimates are broadly consistent with independent evidence on per capita expenditure, state domestic product and real agricultural wages. They show that poverty decline in the 1990s proceeded more or less in line with earlier trends. Regional disparities increased in the 1990s, with the southern and western regions doing much better than the northern and eastern regions. Economic inequality also increased within states, especially within urban areas, and between urban and rural areas. They also examine other development indicators, relating for instance to health and education. Most indicators have continued to improve in the nineties, but social progress has followed very diverse patterns, ranging from accelerated progress in some fields to slow down and even regression in others. Gaiha, Thapa, Imai and Kulkarni (2007) in their analysis of the 61st round of the NSS for 2004-05 confirms higher incidence and intensity of poverty among the STs and SCs, relative to non-ST/SC (Others). A decomposition of poverty gap suggests that a large part of the gap between the ST and Others is due to differences in returns or structural differences while among the SCs it is due largely to differences in characteristics or endowments. Whether these structural differences are a reflection of ‘current’ discrimination is far from self-evident, given the important role of personal identity in determining performance. The policy design therefore cannot be limited to enhancing the endowments of the STs, SCs and other disadvantaged groups. Dubey (2009) examine the interstate disparity in five states in India i.e. Gujarat, Haryana, Kerala, Orissa and Punjab by using NSSO data of 50th round and 61st round. He used three indicators, consumption, inequality and incidence of poverty. Highest level of disparity emerged in Punjab followed by Gujarat and Kerala. Haryana has least disparities only marginally lower than that in Orissa. Singh (2010), in her study examined and analysed the disparities in level of living as measured by monthly per capita consumption expenditure across different income groups in various states in India based on 61st round survey of NSSO. Various measures like gini coefficient and rank for the states in rural and urban areas has been calculated. Disparities in MPCE across income groups are observed in Punjab. Srivastava and Mohanty (2010) in their study used data from the World Health Survey, India, 2003, covering a nationally representative sample of 10,750 households and 9,994 adults, examines the extent of agreement of monthly per capita consumption expenditure and economic proxies (combined with the wealth index) with the differentials in health estimates. Cain, Rana, Rhoda and Tandon, (2010) utilise household-level consumption expenditure data to examine the evolution of inequality during 1983-2004 in India. Various measures of inequality show that inequality levels were relatively stable during 1983-93, but increased during 1993-2004. The increases in inequality have not precluded reductions in poverty, however. They are also more of an urban phenomenon and can be accounted for by increases in returns to education in the urban sector to a considerable extent, especially among households that rely on income from education-intensive services and/or education-intensive occupations. Significance of the study Planning Commission set up an expert group under the chairmanship of Professor Suresh Tendulkar to examine the issue and suggest a new poverty line and estimates. The expert group has considered this issue in detail and has suggested new methodology to arrive at state wise and all-India rural and urban poverty lines for 2004-05, the latest available major National Sample Survey (NSS) round on household consumer expenditure which provides the data base for the calculation of poverty estimates by the Planning Commission. The National Human Development Report 2001 for India (2002) reveals vast differences in human development and poverty between the States of India in 1981. The report notes that “At the state level, there are wide disparities in the level of human development.” (NHDR 2002, page 4). The report also notes that disparities amongst the States with respect to human poverty are quite striking. Socio-economic disparities across the regions and intra-regional disparities among different segments of the society have been the major plank for adopting planning process in India since independence. Even after its impressive performance in the field of science, technology and agriculture during the last three or four decades, a vast majority of Indians are facing the problems of poverty. They are denied even the basic needs of human life like food, safe drinking water, shelter, health, education etc., and are forced to live in a degraded social and physical environment. According to the 61st NSS, the proportion of persons living below poverty line was estimated at 27.5%3 (i.e., more than 315 million people). But, about one third of the population lives under the poverty line of $1 a day, and out of them three in four poor people live in rural areas. Thus, poverty in India is most widespread in the rural areas. Despite a vast range of poverty eradication programmes and several measures adopted in this regard, even after more than 60 years of Independence the situation is still very critical. In recent years, some significant changes have occurred in the poverty alleviation strategy. The Government of India has launched various programmes, such as NAREGA, MNAREGA, Integrated Rural Development Programme (IRDP), Training of Rural Youth for Self Employment (TRYSEM), Development of Women and Children in Rural Area (DWCRA), Wage Employment Programme, National Rural Employment Programme, Jawahar Rozgar Yojana, etc., for the alleviation of poverty. Further, these programmes are now the responsibility of the local bodies (Panchayati Raj institutions) that are expected to improve their performance. But despite all the rigorous efforts, the desired results could not be achieved and considerable level of regional disparities remained in the society. The Structure Adjustment Programme of economic reforms since 1991 with stabilisation and deregulation policies as their central pieces seems to have further widened the regional disparities. Sen 2002 rightly observed that, “the real concern of the so called anti-globalization protesters is surely not globalization per se, for these protests are amongst the most seem to stem in large part from the continuing deprivations and rising disparities in level of livings that they see in current period of globalization. Liberalisation had resulted in the rich becoming richer and the poor, poorer. No State actually got poorer in terms of falling per capita income but the interstate inequality certainly increased  . The seriousness of the emerging acute regional imbalances has not yet received the public attention it deserves. On the basis of above it can be understood that no significant study has been found in the area of disparity in household consumption expenditure for the period 2005-06, 2006-07 and 2007-08 by using NSSO unit level data in India. The NSSO has been collecting data on consumption expenditure on a regular basis for over four decades. Along with other information, it collects detailed information on food and non-food items in a reference period. While majority of the studies happen to be at macro level, this study is a more specific analysis in micro frame by using unit level data household survey conducted by NSSO in India. It is able to lay stress on certain vital issues that needed a more serious discussion. To large extent, the study can be regarded as pioneering one. (iii) Objective of the study: The major objectives of the study are as follows: To know the changes in expenditure structures and consumption patterns during the period 2005-06, 2006-07 and 2007-08 To know the level of household inequality in Indian society in the year 2005-06, 2006-07 and 2007-08. To measure inequality decomposition by regions (states) and sectors (urban-rural) in the society during the year 2005-06, 2006-07 and 2007-08. To know the difference in levels and patterns of household consumer expenditure and across socio-economic groups i.e. caste, religion and family structure in the society during the year 2005-06, 2006-07 and 2007-08. To know the difference in levels and patterns of food and non-food expenditure of across socio-economic groups i.e. caste, religion and family structure in the society during the year 2005-06, 2006-07 and 2007-08. (iv) Methodology Data: Collecting consumption expenditure data is not new in India. The National Sample Survey Organisation (NSSO) conducted an all-India survey of households on participation and expenditure in education, employment, unemployment, migration and consumer expenditure on a regular basis for over four decades. Surveys on consumer expenditure are being conducted quinquennially on a large sample of households from the 27th round (October 1972 – September 1973) of NSS onwards. Additionally, the NSSO has conducted annual consumer expenditure surveys using a smaller sample of households from 1986-87 to 2007-08. In the present study data will be utilised from the three rounds of NSSO consumer expenditure survey i.e. 62, 63 and 64 round collected in the year 2005-06, 2006-07 and 2007-08 respectively .These three consumer expenditure surveys belongs to annual series. Data Analysis: In the present study the inequality in terms of consumer expenditure will be measured in the above mentioned three rounds of survey. Data provided by NSSO is in text document. For the analysis of these unit level data we will use statistical software (STATA). Disparity in terms of MPCE will be calculated for the state wise, region wise, caste, religion and family structure. Different statistical methods (like; descriptive statistics, range, standard deviation, coefficient of variation, Gini coefficient Lorenz curve, Theil’s index, etc.) will be utilised for measuring inequality and disparity. General Entropy Indices and Atkinson Indices are also used for measure of inequality and decomposition of inequality. Graphical presentation of the results will be used for the easy understanding of the data. References: Atkinson, Antony B., (1998), “Poverty in Europe”, Oxford University Press, Blackwell. Bhattacharya, N. and Mahalanobis, B., (1963), “Regional Disparities in Household Consumption in India”, Journal of American Statistical Association, vol. 62, pp 143-161, Blow, L.
Suburbanization and Asian-White Segregation in U.S. Metropolitan Areas Research Paper
assignment helper Suburbanization and Asian-White Segregation in U.S. Metropolitan Areas Research Paper. Introduction The most significant twentieth-century trend is that suburbs became the dominant life style for Americans (Teaford, 2008). Whites experienced overwhelming suburbanization. In 1920, Whites and Blacks lived in suburbs almost equally: about one-third of each group’s residents. However, there was a dramatic increase in suburbanization after WWII. By that time, the Whites suburbanization rate grew by nearly 70%, from a 1940 level of about 38% to a 1970 level of about 63% (U.S. Bureau of Census 1963). The change to suburban dominance in population is reflected in comprehensive statistics on economic activity (Gottdiener and Hutchison, 2011). In many cases, suburbs have outpaced their core central cities in economic importance since 1970. According to the Bureau of Census, 46 percent of the 1990 population lived in suburbia, 40 percent in central cities, and 14 percent in rural areas. This study will examine the association between the level of Asian suburbanization and the segregation between Whites and Asians in 260 metropolitan areas (U.S. Bureau of Census, 1963). Recently, Asians are the fastest growing minority group. According to the Bureau of Census, Asian population grew from 3.5 million in 1980 to 7.3 million in 1990 and to 8.8 million in 1995 (Palen, 1995). Currently, the Asian population consists of around 4% of the entire population (Bureau of Census). There always has been debate as to whether higher level of minorities’ suburbanization yields lower segregation or higher segregation. Segregation is the distribution of racial and ethnic groups into separate and distinct residential areas of the city (Logan, 2011). The general trends in residential dissimilarity across 260 metropolitan areas from whites have declined since 1970. Even though Blacks have experienced the most declines in residential segregation, they remain the most segregated in cities. The largest black population averages remains high. While the Asians remain the least segregated compared to other ethnical groups, the average level of Asian-Whites segregation has not changed much. So the question is why do we care about segregation and why does segregation matter? According to previous social scientists, there are some serious social costs related to residential segregation. This compares to the researches on examining Black-White segregation or Hispanic-white segregation. However, there are not many studies only focusing on Asian-White segregation. Accordingly, a variety of factors affect segregation of Asians but this paper will only focus on the role of suburbanization. By using the data collected from the 260 major metropolitan areas across United States in 2009, the researcher will test the hypothesis that the level of suburbanization leads to the decline of Asian-White segregation based on spatial assimilation model. Theoretical Arguments The purpose of this research is to investigate the association between the level of Asian suburbanization and the segregation between whites and Asians in metropolitan areas. The hypothesis of this research is based on the spatial assimilation model that physical mobility implies one’s upward social mobility. In other words, once Asians social status moving up, then they can get living closer with whites. Therefore, Asians will have less social, economic, and cultural gaps with whites, which finally lead to the decreasing of Asian-Whites segregation. The researcher will put this hypothesis to the test. Additionally, the reputation of Asians towards Whites plays an important role concerning the point of Asian suburbanization increasing the Asian-Whites integration. To restate my hypothesis: the concentration of Asians in the suburbs of the metropolitan area will help to alleviate the Asian-white segregation in the metropolitan area. My theoretical argument is to explain why suburbanization might lead to contact that is more residential with whites. Moreover, the average incomes of Asians are the highest among other minority groups. According to the contact hypothesis, four conditions are especially important. That is urbanization, poverty levels, geographic location, and governments. Some scholars who adapted the stratification perspective state that there is relatively weak correlation exist between the continuously Asian suburbanization and the level of Asian-white segregation in the unit of metropolitan area. According to Logan and Stults’s (2011) report of the New Findings from the 2010 Census, they found that Asians are considerably less segregated than African Americans, and their segregation levels have remained steady since 1980. In addition, with the growth in Asian population, unique ethnic conglomerations tend to coagulate. Because of this, the groups live more sparsely now than in 2000, a trend that has grown since 1980. Despite Asian isolation, another important factor is the stereotypes of Asians. Maria Krysan (2002) conducted an open-ended question survey in Los Angeles, and asked whites about their comfort with different levels of integration with Asians and then asked to explain. Krysan (2002) found the major problem with Asians is based the stereotypes: the modal response was that Asians are not friendly, stick to themselves, or are uninterested in integration. The problems with Asian neighborhoods, according to these whites, are “cultural differences” – particularly expressed as language concerns (Krysan, 2002). Thirdly, the rapid development of suburban Chinatown plays an important role in the controversial issue of continuing Asian-White segregation even in the suburbs. Another study can be looked at is Monterey Park, a suburb outside Los Angeles that became a focal point for new Chinese immigration. In 1960, the population was 85 percent white in contrast to the population in 2000 was 43 percent Asian, 35.5 percent Hispanic, and only 21.6 percent Whites. For a time, the city was known as the “Chinese Beverly Hills”, and it was later referred to as the first suburban Chinatown. Lastly, other sociologists have suspected that the presence of Asian neighbors provides a protection against white flight, or in the terminology of Farley and Frey (1994), a “buffer.” Buffering is shorthand for the argument that the movement of “more fully assimilated second and third generations of Asians to higher-status, more integrated communities” provides “a push that should lead to greater integration of blacks. On the other hand, the spatial assimilation model has remained largely controversial issue in the previous studies, which are related to the possibility that Asians might remain segregated from whites even in the suburbs, from four aspects: Asian isolation, the emerging suburb Chinatown, Asian stereotypes, white flight, and multiethnic buffers. According to Logan and Stults’s report of the 2010 Censes new findings, the rapidly growing Asian populations are as segregated today as they were thirty years ago, and their growth is creating more intense ethnic enclaves in many parts of the country (2011). This paper will focus on the gateway city (this is the city that facilitates entry into the main city), because most of the new Asian immigrants live in suburban towns within the metropolitan region, not in the central city. In addition, our focus on the special assimilation perspective will help us to understand the importance of moving beyond the city and looking at the metropolitan region more broadly when we study immigration and other demographic trends that affect our communities. (Gottdiener and Hutchison, 2011). Hence, while this paper looks into this aspect, it will also delve into the effect of suburbanization on segregation of minority groups with special regard to Asians. Literature Review Large bodies of past researches show the focal relationship between the concentration of Asians in the suburbs of the metropolitan area and the level of Asian-white segregation in the metropolitan area. According to article “Trends in the Suburbanization of Racial/Ethnic Groups in U.S. Metropolitan Areas, 1970 to 2000 (2011:239)”, the authors found that nearly all the variance in 1970 to 2000 growth in White suburbanization (86 percent) is explained by changes in the supply of suburban housing. However, the percentage of variance explained is much lower for the other minority groups. This suggests that the overwhelming cause of changes in White suburbanization over the past three decades was increases in the supply of suburban housing. Another study indicates that Whites have suburbanized faster and more completely than other groups. Hwang and Murdock (1998) concluded that the suburbs possessing seven image indicators: suburb’s smaller population size; lower density; younger housing stock; lower percentage of minority residents; suburb’s old age; higher percentage of traditional family homes and higher percentage of owner-occupied homes did draw more white movers. Massey and Denton’s (1987) cross-sectional analysis of segregation in 1980, reported that in metropolitan areas in which Hispanics or Asians had higher incomes and were more likely to speak English or to be U.S. born, these groups were significantly like to live in suburbs and thereby to experience lower levels of segregation. Moreover, according to Logan et al.’s (2004) finding, they firstly concluded that among Asians, an increasing share of foreign-born persons were associated with greater decreases in segregation. Secondly, if Asian economic standing improves, it will have a great potential to further residential assimilation with whites. Therefore, according to the assimilation model, scholars suggest that discrimination does not fundamentally drive the segregation between Asians and Whites, but the social status and culture differences seems more likely driving the segregation between Asians and Whites. Based on the 2005-2009 American Community Survey (ACS) Logan (2011) found White incomes averaged over $60,000, which is about $25,000 more than blacks and $20,000 more than Hispanics. However, Asian incomes averaged just over $70,000. Thus, if we use the spatial assimilation model, which the economic status increases, it will finally lead to residential assimilation with whites. Obviously, the dramatic increasing suburbanization rates of Whites, Asian prestige (based on statistics) and theoretical expectation based spatial assimilation will create the connection between the two testing variables that the increasing rates of suburbanization will finally lead to the decreasing level of Asian-Whites segregation. Compared to other minority groups, Asians are the least segregated group with whites. Just like Krysan (2002) found, it seems more likely the biggest problem of segregation between Asians and Whites is not about discrimination, but cultural differences . Thus, I assume that Whites hold positive attitudes toward Asian’s reputation, and this finally leads back to the model of assimilation – once we fill the culture gap, this will eventually leads to Asian-Whites integration. The perspective of reputation of a minority group is critical. As long as the reputation stays stable, then if the social status increases and the cultural differences decreases, finally the spatial distance will relatively decreases. In addition, the spatial assimilation model denotes this meaning too. Data and Method In this section, the researcher fast forwards to 2009 using the most recent population census data in 2010. This study tests the relationship between the level of suburbanization in the metropolitan area and the level of Asian-White segregation across 276 metropolitan areas in 2009. In analyzing this focal relationship, I am testing the hypothesis that the higher suburban concentration the lower Asian-White segregation. In other words, there is a negative relationship between suburbanization and Asian-white segregation. The total number sample of metropolitan areas is 276. First, in order to generate a new variable that indicates the percentage of the population living in the suburbs in each of the metropolitan areas, I used the variable of suburban population in 2009 divided by the total population in 2009, then converted into percentage measurement. However, in order to keep the consistency in the sources of data, the number of metropolitan areas changed from 276 to 260. My analysis only includes one measure of a metropolitan-area characteristic, which is the percentage of suburbanization rate in 2009. In terms of the dependent variable, I use an “Index of Dissimilarity” to measure the level of Asian-White segregation; it indicates how evenly the members of Asians and Whites are distributed among the 260 metropolitan areas across the nation. The “Index of Dissimilarity” refers to the percentage of Asians who would have to move in for all neighborhoods to reflect a certain percentage of Asian composition of the entire city (say 46.31 percent). There are five dimensions define geographic traits that social scientists think of when they consider segregation (Gottdiener and Hutchison 2011:213). They are Unevenness, Isolation, Clustered, Concentrated, and Centralized. The percentage of a metropolitan-area population residing in the suburban ring of the metropolitan area is taken from the U.S. Department of Housing and Urban Development’s State of the Cities Data System (2009). The researcher will use correlation analysis to test whether there is a negative association between the level of suburbanization and the level of Asian-white segregation in the metropolitan areas in 2009. The bivariate regression utilizes the relationship between the independent and dependent variables to predict the score of the dependent variable from the independent variable. In other words, after testing the hypothesis by using bivariate regression model, we will be able to predict the level of Asian-white segregation from the level of suburbanization. However, in this study, we are more focusing on the association or relationship between these two variables than prediction. The most common is a Pearson correlation coefficient (r), which is the correlation between two interval variables, and it ranges from -1.00 to 1.00. If -0.3<r<0.3, then we consider it as weak relationship; if -0.7<4<-0.3 or 0.3<r<0.7, then it is considered as moderate relationship; if -1.00<r<-0.7 or 0.7<r<1.0, then we interpret it as strong relationship. Results Results from model predicting the level of suburbanization has very weak positive association on Asian-White segregation in 2009 in 260 metropolitan areas across the United States. This is completely opposite to the hypothesis. The correlation coefficient arrived at from the regression model is 0.0121. This indicates a weak but positive relationship between the variables. Therefore, the level of suburbanization almost has no effect on the level of Asian-white segregation in 2009 across 260 metropolitan areas (n=260). Obviously, the result does not support my hypothesis that there is a negative association between the level of suburbanization and the level of Asian-white segregation. This shows that other factors are also at play in affecting the segregation of Asians. This may include poverty levels, demographic shapes, levels of immigration, social status, and state and federal policies. While suburbanization plays a role in segregation, the factors appear more pronounced as they form a larger chunk of the explanatory model (Timberlake et al. 2011). Moreover, the bar graph interprets the level of Asian-white segregation are all under 50, which means modest segregation. An interesting finding in the bar graph shows that the modest level of suburbanization actually has higher Asian-whites segregation than the lowest and highest level of suburbanization. The result implies that segregation tends to categorize things into certain groups that look alike. This actually supports my counter theoretical argument that Asians might remain segregated from whites even in the suburbs. For example, while Chinese are of Asian descent, suburban Chinatowns seem to be resided by Chinese only. This is despite the fact that there may be black population residing alone and whites alone in the same locality. Discussion The United States has traditionally been referred to as a “melting pot”. Her history began with waves of immigrants; bring their own cultures, traditions and all hoping to find freedom, new opportunities, and a better way of life. The racial segregation has a long history in the United States: from the Black Codes to Chinese Exclusion Act to Japanese American internment to Jim Crow Laws to Redlining to Separate but Equal to White flight. As we can see, the state of segregation has been changed from legally enforced separation to more voluntary or involuntary separation. The result shows that the increasing suburbanization does not have big effects on Asian-white segregation. However, it has a slight influence on bringing up the segregation of Asian and Whites. Therefore, the question as to whether suburbanization created more opportunities for living the “American Dream,” lingers. On the other hand, it is prudent to ask whether suburbanization led to the homogenization of American culture, which produces more segregation and isolation. As I already argued at the beginning, too many unmeasured variables affect segregation of Asians. For this study particularly, I only focus on the role of suburbanization (Lu, 2001). The results explain my hypothesis that suburbanization might not be the only factor that cause the Asian segregation. Therefore, in spite of suburbanization, what are the other factors affect segregation of Asians? According to Park and Iceland’s (2011) findings of residential segregation from 1990 to 2000, Asian segregation levels are consistently lower in new destinations. Moreover, the native-born are less segregated than the foreign born, which is consistent with immigrant spatial incorporation. Finally, socioeconomic indicators are generally consistent with predictions of spatial assimilation. This study posits several academic and procedural limitations. First, lack of independent variables causes spuriousness. Secondly, there lacks available data to support Asian segregation. Thirdly, this study only observes one year (2009), which is too short for studying segregation. Usually, sociologists often study segregation for at least a decade or even longer periods, so they can gather more data and come up better patterns. Data availability has the capacity to bring studies that are more empirical. Additionally, it is possible to relate to different periods to study patterns. References Gottdiener, M.Suburbanization and Asian-White Segregation in U.S. Metropolitan Areas Research Paper
Create a personal Code of Ethics that you live and work by. A Code of Ethics can encompass all
Create a personal Code of Ethics that you live and work by. A Code of Ethics can encompass all types of areas – from how you treat others as you want to be treated, the golden rule, guidelines you had growing up and want to pass on to others, to how you need to act in the workplace and serve patients in their time of need. Be creative, think outside of the box and let your conscious be your guide. I would suggest looking up a Code of Ethics for your current job or employment area as examples. You would be surprised how many Code of Ethics there are out there. Please also see the example in this module for the ACHE Code of Ethics. Please ensure that you correctly cite within the code if references have been utilized. Please remember to include a title page, reference page and rubric in the assignment. Paper should include at least 400 words – this should not simply just be a list of “I wills”
Campbellsville University Portfolio Execution Assessment & APT Model Discussion
Campbellsville University Portfolio Execution Assessment & APT Model Discussion.
I’m working on a writing discussion question and need an explanation to help me study.
1. Discuss style portfolios. How is their performance measured?2. David McClemore, the CFO of Ultra Bread, has decided to use an APT model to estimate the required return on the company’s stock. The risk factors he plans to use are the risk premium on the stock market, the inflation rate, and the price of wheat. Because wheat is one of the biggest costs Ultra Bread faces, he feels this is a significant risk factor for Ultra Bread. How would you evaluate his choice of risk factors? Are there other risk factors you might suggest?
Campbellsville University Portfolio Execution Assessment & APT Model Discussion
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