Different researchers have used education, income, and occupational class to predict social welfare outcomes and to demonstrate the effects of socioeconomic determinants of health on social mobility (Gates, 2014; Friis, 2009). Most of such studies are concentrated in the areas of health inequality. Scholars have often referred to one variable as a replacement, or support, for another (Gates, 2014; Friis, 2009). For example, differences in educational levels in one study have been used as a support pillar for other studies that acknowledge income differences when predicting social mobility factors. Similarly, there are cases where adjustments for social class made in one study could provide the basis for using education in a regression analysis.
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Friis (2009) says that using the three variables interchangeably has been justified, based on the understanding that they could measure the same dimension of social mobility. For example, the deprivation of material wealth could easily be reflected in variations in social class. The consistency of using these variables to explain social mobility demonstrates that they can measure the same phenomenon. However, there is a lack of clarity surrounding certain concepts of the worker class, socioeconomic groups, and social status. Similarly, there is a predominant effect noted concerning variations in educational and income groups. Indeed, as Gates (2014) contends, there is increased caution regarding the interchangeability of these indicators when predicting factors affecting social mobility. In this proposed study, we intend to explore the relationship between income and that of worker class and educational levels among adult Hawaiians.
Although many studies have used income, education level, and the working class as indicators of social mobility, few studies have contextualized this relationship among adult Hawaiians. Our research topic is based on exploring the relationship between income, worker class, and education level among adult Hawaiians. The research group would be adult residents in Hawaii, while the dependent variable would be income (annual wages or salary). Lastly, the independent variables would be the worker class and education level. The existing research gap is centered on explaining whether there is an association between the dependent variable and the independent variables.
Review of Current Literature
- Lacour and Tissington (2011) investigated the effects of poverty on academic achievement and found that poverty negatively affected educational achievement because of the lack of resources needed for academic excellence. This paper will be useful in our research study because it could help us to understand the relationship between income, worker class, and education levels.
- Wannakrairoj (2013) investigated the relationship between education levels and experience in Thailand by comparing the differences in labor market outcomes between workers living in urban and rural Thailand. He found that education and experience had a significant impact on wages. This paper will be useful to our analysis because it will help us to understand the relationship between two variables in our analysis – education, and income.
- Tackey, Barnes, and Khambhaita (2011) explored the relationship between poverty, ethnicity, and education and found that different ethnic groups, from the same socioeconomic background, had different outcomes, in terms of income potential and educational levels. The findings of this paper will be useful in our research topic because they may help us to understand the relationship between worker class (which is denoted by poverty) and education.
- Rothwell (2013) explored the pathways to higher education among native Hawaiians and explained how these networks affected income levels and social status within the studied population. The researchers found that Hawaiians had low income and education standards because of colonization and historical injustices. This research is important for our analysis because it would help us to understand the relationship between education levels and worker class within a cultural context of native Hawaiians, which is our research group.
- Erola, Jalonen, and Lehti (2016) explored the relationship between parental socioeconomic status and their children’s education standards and class. They found that parental education and socioeconomic status influenced their children’s education and socioeconomic status. They also found an overlap in income, education, and class variables. This paper will be useful in our investigation surrounding the impact of education standards, income, and worker class.
The research design for the proposed study would be quantitative because we are basing the research on pre-existing quantitative data contained in the dataset for Hawaii 2005 housing report, cited in the United States Census Bureau (2016). Furthermore, the research variables (income, educational level, and social class) are measurable, thereby fitting in the quantitative framework (Doolan & Froelicher, 2009).
Variables and their Measurement
As mentioned in this report, the variables under study would be income (WAGE_GP) as the dependent variable and educational level (SCHL) and worker status (COW) as the independent variables. Each variable will have a unique level of measurement. The educational level will have 16 values, with the least value (1) being the failure to complete any level of schooling and the highest value (16) being a doctorate. The class of workers will be measured using nine metrics that cover different classes of workers (United States Census Bureau, 2016).
The rationale for Limiting Variables
I will constrain myself to the three variables mentioned above (income, education level, and working-class) because these are the main social mobility factors highlighted by many researchers. Indeed, as mentioned in the first section of this paper, researchers have used them as reliable socioeconomic determinants of social mobility. Furthermore, I believe that they are sufficient for exploring the research topic because they are the main pillars of socioeconomic development in society.
Doolan, D., & Froelicher, E. (2009). Using an existing data set to answer new research questions: A methodological review. Research & Theory for Nursing Practice, 23(3), 203-215.
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Erola, J., Jalonen, S., & Lehti, S. (2016). Parental education, class and income over early life course and children’s achievement. Research in Social Stratification and Mobility, 44, 33-43.
Friis, A. (2009). Epidemiology for public health practice. New York, NY: Jones & Bartlett Publishers.
Gates, N. (2014). The concept of race in natural and social science. London, UK: Routledge.
Lacour, M., & Tissington, L. (2011). The effects of poverty on academic achievement. Educational Research and Reviews, 6(7), 522-527.
Rothwell, D.W. (2013). Pathways to higher education for native Hawaiian individual development account participants. The International Indigenous Policy Journal, 4(4), 1-18.
Tackey, N., Barnes, H., & Khambhaita, P. (2011). Poverty, ethnicity and education. Web.
United States Census Bureau. (2016). Hawaii. Web.
Wannakrairoj, W. (2013). The effect of education and experience on wages: The case study of Thailand in 2012. Southeast Asian Journal of Economics 1(1), 27-48.