Microsoft Word - 1TerryHolt_Reviewed_SG_TD.docx CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) The Effect of Race on Poverty and the Equality of Minorities Terry Holt Department of Sociology California State University, Los Angeles Using General Social Survey (GSS) data from 1972 to 2004, this study considers if racial discrimination continues to represent a significant barrier for the economic advancement of African Americans and other minorities in the U.S. compared to whites. Specifically, does race affect income equality? Bivariate analysis and Logistic Regression analysis indicate that the “total family income average” for Blacks is significantly less compared to Whites, and Blacks are more likely to live in poverty (income less than $25,000) than Whites. Conversely, when it comes to other minority groups, there is no significant difference in “total family income average” compared to Whites. In addition, the findings also suggest that women are far more likely to live in poverty than men, as one’s gender has a significant effect on one’s income earning potential. INTRODUCTION 1Racism has existed throughout human history, and it continues to represent significant problems for many people in the United States. Racism is the belief that one’s race is primarily the determining factor that reflects human traits and capacity. Racist ideology generally supports the premise that a particular race is either superior or inferior to another, and that a person’s 1. Terry Holt is a graduate student at the Department of sociology. His paper was originally submitted to SOC 410 Advanced Statistics, taught by Professor Hyojoung Kim in Summer 2009. social and moral qualities are pre- determined by his or her inborn biological characteristics. The distinction of racial differences gives way to the belief of an inherent superiority of a particular race while simultaneously ordering other races in a hierarchy. Institutional racism causes a large numbers of individuals who are deemed inferior to be denied even the most basic human rights. Conversely, individuals who belong to the group that is deemed superior have historically been elevated to positions that allow them to enjoy preferential treatment. Why do people from one social group oppress and discriminate against people from other social groups; and why is it so difficult INCOME INEQUALITY by Terry Holt 2 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) to eliminate? This study investigates whether racial discrimination continues to represent a significant problem for African Americans and other ethnic minorities in the U.S. Some race theorists assert the pessimistic view that racism is permanent and that policy reforms will not curtail the development of racial distinction and antagonisms. Racial inequality has become an enduring and deeply regimented way of knowing and organizing the social world, and thus is unlikely to be completely eliminated. The African- American experience in the United States has enriched the fabric of American history and society in a myriad of ways, many of which have only recently been recognized. However, the overarching theme of African- Americans and other minority groups’ experience has been one of misery, exploitation, inequality, and discrimi- nation. It is to this end, that those who wish to understand the minority experience in America ask themselves following question: Are minorities making progress in the United States? Is there any significant gap in the income of African Americans and other minorities compared to those of Caucasians in the United States, and what ethnic minorities are more likely to live under the poverty level? If we find that a particular ethnic group is more likely to live in poverty compared to Whites, then, one might conclude that racism continues to remain a significant obstacle for the economic advancement of the aforementioned minority groups. In addition to race, this study will also consider the impact of age, gender, religion, political affiliation, educational attainment, and the number of years spent obtaining formal education and training with respect to relative income and those who live in poverty. Poverty is defined as the total family income level of respondents that falls at or under 25,000 annually. LITERATURE REVIEW Recent battles regarding civil rights and race discrimination in the United States were fought on two fronts: legal, and the public’s perception of race. Legal fronts consisted of lawsuits and amended legislation prompted institutions such as schools, banks, and government agencies to lessen race discrimination. Brown vs. Board of Education, the Civil Rights Act of 1964, and other subsequent battles brought race discrimination to the attention of the American public. The former front involves the public’s perception of race. Henry and Sears (2002) argue that public sentiments concerning African- Americans are governed by a psycho- logical blend of negative feelings and conservative values, particularly, the belief that African-Americans violate cherished American values. The public’s per- ception of African-Americans is rooted in an abstract system of early learned moral values and ideas that typically view African-Americans as social misfits. Racial conflict has plagued the United States since its inception; in particular, it has been primarily driven by racial prejudice of African-Americans (Allport 1979). While overt forms of racial discrimination such as “Jim Crow” segregation have been eliminated in the United States, and whites’ opinions regarding racial issues have become INCOME INEQUALITY by Terry Holt 3 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) more liberal, racial discrimination remains a significant difficulty for many ethnic minority groups. Moreover, current research shows that racism has evolved from these overt forms of Jim Crow segregation (older belief systems which incorporated social distance between the races). One form of research has been developed around the basic idea that new forms of racism have taken root in America, which is the symbolic racism theory (Sears 1988). According to Kender and Sears (1981), symbolic racism is commonly described as a coherent belief system, which supports concepts that racial discrimination is no longer a valid point of contention for African Americans, and that their disadvantage stems from personal ir- responsibility, and thus their continual demand for equal treatment is not valid. Proponents of liberal optimism, on the other hand, contend that viable solutions to our nation’s race problems are possible. Robert Parks (1950) clearly articulates key concepts of the race relation cycle. He argues that race relations develop in a four cycled stage: contact, conflict, accommodation, and assimilation. The first stage occurs when two or more different races of people come together, and they are obliged to interact with each other. Competing for scarce resources they fall into conflict, which eventually gives way to accom- modation, where a stable but antagonist social order fosters a social hierarchy. Finally, Parks asserts that accom modation is attained when different races assimilate through a process of cultural and physical merging. The end result of such a merger is the development of one homogenous race, where class supersedes race as the primary focal point of social distinction. Parks ascertains that race relations invariably pass through the previously mentioned stages, and that the present location of a particular race of people offers strong evidence to suggest the kind of social experiences that a particular race of people will encounter not only their past but also the future path. The American society, like many others throughout the world, is organized by powerful dynamics that are often very difficult to interrupt. Privilege is a predictable precursor for such things as race distinction, because the privileged group must distinguish itself from other groups. Distinctions based on race may not always be carried out with malicious intent, however, to suggest that the effects of such characterizations are inconsequential, definitely deserves examination. But, how are we to understand the realities that both produce such distinctions and the ensuing consequences that they in- variably produce? Do we view them as purely accidental, or as oddities that simply seem to happen? Or is race, in fact, reflective of designed dynamics that are sown into the very fabric of our society? DATA AND VARIABLES In order to empirically examine whether or not race remains a significant barrier for the equality of ethnic minorities in the United States, this researcher uses General Social Survey (GSS) data. The GSS was designed as part of a data diffusion project in 1972. The GSS replicated questionnaire items and wordings are used in order to facilitate INCOME INEQUALITY by Terry Holt 4 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) time and trend studies. This data collection includes a cumulative file that merges all data collected as part of the General Social Services Surveys from 1972 to 2004. The 2004 survey was composed of permanent questions that appeared on two out of every three surveys and a small number of occasional questions that occurred in a single study. There were a total of 2,812 respondents RESEARCH HYPOTHESES The Dependent Variable: Income Level A comparative level of income between whites (the comparison group), African Americans and other ethnic minorities over time will demonstrate whether racism remains a central hindrance to the advancement of minorities in the United States. That is, I hypothesize that Caucasians will show a higher mean income from that of minorities and, therefore, a lowered propensity for having a total family income of 25,000 dollars or less. If racial equality is present between races, then, we can expect to see a somewhat uniform distribution of income between the different ethnic groups and an average number of people in different races living in poverty. However, if we see a significant difference between mean incomes of different ethnic groups, then, we assume that there is no real equality. The continuous variable income was converted to a dichotomous variable (because of a skewed distribution of income), where if respondent’s total family income is 25,000 or less, then, they are considered to live in poverty; conversely, if the respondent’s total family income was above 25,000 dollars per year, then they are coded as not being in poverty. Income level is measured by the GSS variable (VAR: INCOME). Respond- ents were asked, “In which of these groups did your total family income, from all sources, fall last year before taxes that is?” A fifteen point response category was used to capture respondent’s answers: under $1,000; $1000 to 1,999; $2,000 to 2,999; $3,000 to 3,999; $4,000 to 4,999; 5,000 to 5,999; $6,000 to 6,999; $7,000 to 7,999; $8,000 to 8,999; $9,000 to 9,999; $10,000 to 14,999; $15,000 to 19,999; $20,000 to 24,000; $25,000 or over; refused; don’t know, no answer; not applicable. The variable “INCOME” was converted into a dichotomous variable: 1) 1= living in poverty (income $25,000 or less) 2) 0= not living in poverty (income above $25,000). The Key Independent Variable: Race The mere distinction of individuals by race invariably gives way to the belief that slight biological differences between certain groups of people predetermines the worth, intelligence, value, and other aspects of a person’s being. As a consequence, race distinction is typically followed by the formation of preset stereotypes regarding a particular group of people and the creation of a racial hierarchy. Distinction by race has been the catalyst throughout mans history for wars as well as hate-crimes, and it has caused untold human suffering not only in the U.S. but, indeed, throughout the entire world. It is this author’s hypothesis that race continues to plague INCOME INEQUALITY by Terry Holt 5 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) minorities in the U.S. Race is measured by the GSS variable (VAR: RACE). Respondents were asked, “What race do you consider yourself?” Respondents were asked to select their appropriate race from a three-point scale: White, Black, or other (specify). The key independent variable “RACE” was dichotomized as follows: 1) Black or not, and 2) Other race or not. Other Independent Variables: Age It is my hypothesis that the working age of an individual will be positively correlated with a higher mean income. That is, when people begin to work they will often start at the low end of the pay scale in their respective occupations. However, as they gain more experience on the job, their worth to their employer increases, and thus they can demand higher incomes. Age is measured by the GSS variable (VAR: AGE). Respondents were asked to indicate their age by selection from the approximate eight point choice category. The categories are listed as follows: 10-19 years of age (y.o.a.), 20-29 (y.o.a.), 30-39 (y.o.a.), 40-49 (y.o.a.), 50-59 (y.o.a.), 60-69 (y.o.a), 70-79 (y.o.a), 80 or over, and No answer/don’t know. REMARKS: Respondent’s age: Data has been recoded into actual age in cols. 92 and 93. See Appendix D, and Appendix E. Age distribution, for the detailed response. The distribution for the first digit, col. 92 is given below. See Appendix N for changes. Gender Not only is income level stratified along racial dimensions, but also by gender. Traditionally, the U.S. has always exercised patriarchal domination, and, as such, men have characteristically held more prestigious employment positions that typically pay more. Therefore, I hypothesize that the mean income of men will be higher than that of women. Gender is measured by the GSS variable (VAR: SEX). Code respondent’s sex: they were asked to indicate their gender by using the following two point response category: “Male, Female;” Male=1, female=2. Education Level I hypothesize that higher levels of education will be positively correlated with a higher mean income. Individuals, who have higher levels of education, will be more valuable to their employers because of special training, job skills, and knowledge, which will allow them to perform specialized tasks. Education is measured by the GSS variable (VAR: DEGREE). Respond- ents were asked, “What is your highest level of education?” Respondents were asked to select their appropriate education level from a six-point scale which is listed as follows: 1) Less than high school, 2) High school, 3) Associate/ junior college, 4) Bachelor’s, 5) Graduate, and 6) Don’t know. Religion One was Raised with I hypothesize that those individuals who were raised in families that regularly attended religious services as children INCOME INEQUALITY by Terry Holt 6 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) will have a stronger work ethic, than those who did not; consequently, those individuals who were raised with religion will possess a higher mean income than those respondents who were not raised in a family that attended religious services. Religion is measured by using the GSS variable (VAR: RELIG16). Respondents were asked, “In what religion were you raised?” Respondents were asked to select the religion they were raised in by making a selection from the following five-point choice selection category: Protestant, Catholic, Jewish, none, other (specify religion, and/or church denomination. The variable “RELIGION” was dicho- tomized as follows: 1) Jewish or not, 2) Catholic or not, 3) Protestant or not 4) Other religion or not, and “None” or not raised with any religion is the comparison group. Political Affiliation I hypothesize that those respondents who are Republicans (who typically hold more traditional values) will be more positively correlated with higher mean income levels than those of other political affiliations. This argument is not strong enough Political affiliation is measured using the GSS Variable (VAR: PARDYID). Respondents were asked, “Generally speaking do you usually think of yourself as Republican, Democrat, Independent, or what?” The variable “PARDYID” was dichotomized as follows: 1) Democrat or not 2) Independent or not 3) Other political party or not. THE FINDINGS Figures 1, 2, and 3 report the frequency distributions for the main variables used in Analysis. A. Frequency Distribution of the D.V. and the Key I.V. The main hypothesis of this paper singles out the dependent variable as total family annual income (VAR: INCOME), and this continuous variable was converted into a dichotomous variable: 1) respondents whose total family income was 25,000 dollars or less are considered to be in poverty, and they were coded as “1”; and 2) those respondents whose total family income is above 25,000 dollars were coded as “0,” and they are considered not in poverty. There were a total of 2,812 respondents. 1, 764 respondents (71.1%) reported that their total family income was $25,000 or more (not in poverty), and 718 respondents (28.9%) reported that their total family income was below $25,000 (in poverty), and 330 (11.7%) respondents showed missing data for this question. The Key Independent Variable Race The key independent variable for this study is race (VAR: RACE), and this nominal variable was dichotomized as follows: 1) Black or not, 2) Other race or not (White is the comparison group). The frequency distribution for “Black or not” is as follows: there were a total of 2,812 respondents in this study, 377 of whom (13.4%) reported that they were Black; 2,482 respondents indicated that INCOME INEQUALITY by Terry Holt 7 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) they were not Black, and 333 respondents failed to answer the question. The frequency distribution for “Other race or not” is as follows: 2812 respondents took part in the survey, and 201 persons reported that their race was “Other” (7, 1%), and 2,611 respondents reported that their race was not “Other.” B. Univariate Statistics Table 1 reports the frequency distribu- tions for all the variables used in Analysis. The dependent variable “INCOME” was converted to a dicho- tomous variable (in poverty or not) and it has a frequency of 2482, a mean of 0.2893, and a standard deviation of 0.45352. Most respondents in the survey had incomes that were 25,000 or more (not in poverty). The key independent variable “RACE” was dichotomized as follows: Black or not, and Other race or not (Whites are the comparison group). The frequency for “Black or not” is 2812 with a mean of 0.1341 and a standard deviation of 0.34079. The frequency for “Other race or not” is 2812 with a mean of 0.0715 and a standard deviation of 0.25767. “AGE” has a frequency of 2803, a mean of 45.96, and a standard deviation of 16.1801. “RESPONDENTS’ SEX” has a frequency of 2812, a mean of 1.54, and a standard deviation of 0.498. “RS HIGHEST DEGREE” has a frequency of 2811, a mean of 1.61, and a standard deviation of 1.207. “RELIGION One was RAISED With” was dichotomized as follows: 1) Jewish or not, 2) Catholic or not, 3) Protestant or not, and 4) Other religion or not (No religion is the comparison group). “Jewish or not” has a frequency of 2809, a mean of 0.0228, and a standard deviation of 14924. “Catholic or not” has a frequency of 2801, a mean of 0.2960, and a standard deviation of 45656. “Protestant or not” has a frequency of 2801, a mean of 0.5598, and a standard deviation of 49650. “Other religion or not” has a frequency of 280, a mean of 0.0421, and a standard deviation of 20092. “PARTYID” was dichotomized as follows: 1) Democrat or not, 2) Independent or not, and 4) Other political party (no political affiliation is the comparison group). “Democrat or not” has a frequency of 2800, a mean of 0, 3425, and a standard deviation of 0.47463. “Independent or not has a frequency of 2800, a mean of 0.3539, and a standard deviation of 0.47827. “Other political party or not” has a frequency of 2800, a mean of 0.0104, and a standard deviation of 0.10126. INCOME INEQUALITY by Terry Holt CALIFORNIA SOCIOLO Terry Holt CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: Figure 1 Figure 2 8 1-17) INCOME INEQUALITY by Terry Holt CALIFORNIA SOCIOLO Terry Holt CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: Figure 3 9 1-17) INCOME INEQUALITY by Terry Holt 10 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) Table 1 Frequency Distribution Variables Survey Questions Response Categories Freq Mean S.D. Income In which of these groups did your total family income fall? 0= Not in Poverty 1= In Poverty 2482 .2899 .4535 Race What race do you Consider yourself? 1= White or not 2812 1.28 0.586 2= Black or not 2812 .1341 .3408 3= Other Race or not 2812 .0715 .2577 Age Select you age 1=10 to 19 2=20 to 29 3=30 to 39 4=40 to 49 5=50 to 59 6=60 to 69 7=70 to 79 8=80 or over 2803 45.96 16.18 Sex Select your sex 1=male 2=female 2812 1.54 0.498 Degree What is your highest Level of education? 1=Less than High school 2=High school 3=Junior college 4=Bachelors 5=Graduate 6=Don’ know 2811 1.61 1.207 Relig16 In what religion were you raised? 1= Jewish or not 2809 .0228 1492 2= Catholic or not 2801 .2960 4566 3= Protestant or not 2801 .5598 4565 4= Other religion or not 2801 .0421 2009 Pardyid In which political party are you affiliated with? 1=Democrat 2800 .3425 .4746 2= Independent or not 2800 .3530 .4783 3= Other Pol. Party or not 2800 .0104 .1013 INCOME INEQUALITY by Terry Holt 11 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) C. Pearson’s Correlation Analysis Table 2 reports the bivariate associations (Pearson’s correlation) for all the variables used in Analysis. As hypothesized, Pearson’s correlation supports the premise that the total family income of Blacks, on average, is likely to fall at or below 25,000 dollars (poverty). Pearson’s correlation is 0.175 (very significant); therefore we reject the null hypothesis and accept the alternative. That is, there is a significant difference between the average total families incomes of Blacks compared to Whites. Other races appeared to earn slightly more than Whites. Pearson’s correlation for Other is -0.003. Therefore, we fail to reject the null hypothesis for Others, and conclude that there is no significant difference between the average total family incomes of others as opposed to Whites. Pearson’s correlation for income and other political party is -0.029, indicating a slight decrease in the number of other political party members who have a total family income of 25,000 dollars or less. Therefore, we fail to reject the null, and conclude that other political party affiliation does not significantly affect the total family income of these respondents, as opposed to Republicans. Pearson’s correlation between poverty and Democrats shows .064. Therefore, we reject the null, and accept the alternate hypothesis; Democrats are significantly more likely to show a family income of 25, 0000 or more a year. Democrats are less likely to have a total family income of 25,000 dollars or less. Pearson’s correlation between Independent party and poverty is -0.064, which is significant; therefore, we reject the null hypothesis and accept the alternative hypothesis. Independent party membership has a significant effect on poverty. That is, Independent party members are more likely to have total family incomes of 25,000 dollars or less. Pearson’s correlation between the Jewish religion and poverty is -.052 which is significant. Therefore, we reject the null hypothesis and accept the alternative hypothesis. We conclude by stating that respondents who are Jewish are more likely to have a totally family income that is above 25,000 dollars. Pearson’s correlation for Catholics is -0.55, which is significant. Therefore, we reject the null hypothesis, and conclude that Catholics are less likely to show a total family income of less than 25,000 dollars. Pearson’s correlation for Protestants is -0.028, which is insig- nificant. Therefore, we fail to reject the null hypothesis and reject the alternative hypothesis. We conclude that respond- ents who are Protestant are not likely to have incomes below 25, 0000 dollars. Pearson’s correlation between other religions and poverty is 0.017, which is statistically insignificant. Therefore, we fail to reject the null hypothesis and reject the alternative hypothesis. Respondents who are coded as having Other political affiliation are not likely to have total family incomes below 25,000 dollars. INCOME INEQUALITY by Terry Holt 12 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) Table 2. Pearson’s Coefficients of Variables Used in the Analysis *P<0.05; **P<0.01 (two-tailed tests) The main limitation of Pearson’s correlation is that the observed relationship between the dependent variable “In poverty or not” may be spurious due to the effects of other variables in the analysis. The multivariate analysis enables us to address such spurious relationships that may arise due to other control variables in the model. I used a dichotomous logistic analysis because the dependent variable “Income” was converted to a dichotomous value (In poverty or not). Logistic regression analysis was performed using a dichotomous dependent variable: 1= “In poverty and 0= “Not in poverty.” An OLS binary regression test was performed and it yielded the following results (see table 3). The likelihood ratio test is statistically significant at .05 levels. Therefore, we reject the null hypothesis; that is, none of the independent variables has a significant effect. The reported R-square is .2093, meaning that roughly 21-percect of the variance in the latent dependent variable is captured by the model. The regression coefficient of “Black or not” is positive and significant at the .05 level, net the other variables in the model. Therefore, we conclude that being Black does significantly affect one’s income earning potential, and thus Blacks are more likely to live in poverty than Whites. The regression coefficient of “Other race or not” is positive and insignificant, net the other variables in the model. Therefore, we conclude by stating that there is no significant difference between Whites and Other 1 In Poverty or Not 2 Black or Not 3 Other Race 4 Other Pol. Party 5 Demo. or not 6 Indep. or not 7 Jewish or Not 8 Catholic or not 9 Protestant or not 10 Other Religi on In Poverty or not Delete This Row Black or not .174** Other Race -,003 -.109** Other Pol.Party -.029 -.020 -.015 Democrat .064** .269** .000 -.074** Independent .061** .059** 089** -.076** -.534** Jewish or not -.052** -.060** -.024 .032 .071** -.038* Catholic or Not -.055** -.191** .121** -.012 .001 .029 -.096** Protestant or not -028 .201** .198** .-.009 -.063 -.063** -.167** -.731** Other Religion .017 .001 .225** .-.004 .031 .031 -.031 -.136** -.231** INCOME INEQUALITY by Terry Holt 13 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) races in their probability of being in poverty. Persons who are of other racial groups are not significantly more likely to live in poverty than Whites. Of course, this offers an interesting paradox that is exactly why some minority groups fair better finically than others. The regression coefficient of “Age” is positive and insignificant. The effect of age was found to have no significant effect on one’s income earning potential; therefore, we fail to reject the null hypothesis, and reject the alternative hypothesis. We conclude by observing that one’s age does not significantly affect one’s earning potential. The regression coefficient of “Sex” is positive, and it was found to be highly significant. Therefore, we reject the null hypothesis and accept the alternative hypothesis. We conclude by noting that one’s gender has a very significant impact on earning potential. Finally, women are statistically much more likely to live in poverty than men. The regression coefficient of “In poverty or not” and “RS Highest degree” is negative and quite significant at the .05 level, net the other variables in the model. Therefore, we reject the null hypothesis and accept the alternative hypothesis. We conclude by asserting that respondent’s educational level has a very significant impact on one’s income earning potential. Finally, we conclude that respondents who obtained higher levels of education are less likely to live in poverty than the less formally educated person. The regression coefficient of “Jewish or not” is negative and statistically insignificant. Therefore, we fail to reject the null hypothesis, and we reject the alternative hypothesis. Further, we conclude that the probability that one’s income is not statistically impacted by the fact that they are Jewish. That is, being Jewish does not appear to affect one’s chances of living in poverty, as opposed to individuals who were not raised in any religion. The regression coefficient of “Catholic or not” is negative and very statistically significant. Therefore, we reject the null hypothesis and accept the alternative hypothesis. The relationship between living in poverty and Catholicism shows that individuals who were raised catholic are less likely to live in poverty than those who were not raised in any religion. As hypothesized, individuals who were raised in Christian based religion have a stronger work ethic than people who were raised with no religious belief. The regression coefficient of “In poverty or not” and “protestant or not” is negative and significant. Therefore, we reject the null hypothesis and accept the null hypothesis. We conclude by asserting that people who were raised in the Protestant religion are significantly less likely to live in poverty than individuals who were not raised in any religion. Again, we see that people who were raised with religious belief are less likely to live in poverty than those who were not; this could of course be explained by my hypothesis that individuals who were raised with strong religious beliefs are more likely to have a stronger work ethic, thereby making them less likely to live in poverty. The regression coefficient of “In poverty or not” and “Other religion” is negative and statistically insignificant. Therefore, we fail to reject the null, and INCOME INEQUALITY by Terry Holt 14 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) we reject the alternative hypothesis. We conclude by stating that there does not appear to be a significant relationship between living in poverty and individuals who were raised in other religious beliefs, as opposed to those who were raised with no religious belief. This finding could be explained by the fact that many other religions are not Christian based, which would support my hypothesis. The regression coefficient of “In poverty or not” and “Other Political Party” is negative, and it is statistically insignificant. Therefore, we fail to reject the null hypothesis and reject the alternative hypothesis. We can conclude by stating that other political party members are not more likely to live in poverty than Republicans. The regression coefficient of “In poverty or not” and “Independent Party or not” is positive and highly statistically significant at the .05 level. Therefore, we reject the null hypothesis and accept the alternative hypothesis. We conclude by asserting that people who are Independent party members are much more likely to live in poverty than Republican (as hypothesized). The regression coefficient of “In poverty or not” and “Democrat or not” is positive and very statistically significant. Therefore, we reject the null hypothesis and accept the alternative hypothesis. We conclude by stating that people whose political preference is associated with the Democratic Party are more likely to live in poverty than their Republican counterpart. D. Logistic Model Selection for Dichotomous D.V. Table 3. Model Fit Statistics of Binomial Analysis Independent Variables Coefficients Standard Error Constant Black or not Other Race or Not Age Sex RS Highest Degree Jewish or Not Catholic or Not Protestant or Not Other Religion Other Political Party Independent or Not Democrat or Not -0.786 0.744 0.063 0.005 0.404 -0.728 -0.724 -0.507 -0.382 -0.058 -0.081 0.481 0.406 (0.274)** (0.142)** (0.195) (0.003) (0.098)** (0.052)** (0.464) (0.186)** (0.176)* (0.282) (0.595) (0.127)** (0.133)** Likelihood Ratio Chi-Sq. 390.482** Nagelkerke R-Square .209 *P<0.05; **P<0.01 INCOME INEQUALITY by Terry Holt 15 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) CONCLUSION To examine how the independent vari- able “In Poverty or Not” is affected by the independent variables (race, age, educational level, religion, and political affiliation), we first examined the frequency distribution of all variables in the study, see table I. Table II shows the relationship between the dependent variable and each of the independent variables using Pearson’s correlation. Pearson’s correlation indicates the strength and direction of a linear relationship between two random variables; in this case, the dependent variable “in poverty or not” and all independent variables are compared while negating the affect of other variables Logistic Regression Logistic regression was performed on all the variables in the model (see table 3) The findings above can be viewed as both encouraging and as a source of concern. On one hand, we can clearly see that most people in the United States have total family incomes above $25,000—that is most people in the U.S. are not living in poverty. On the other hand however, as hypothesized, there is reason for concern regarding the relative income of African-Americans in the U.S. Despite the efforts of civil rights leaders in the turbulent years of the 1960s and laws enacted to promote racial equality, African-Americans are currently far more likely to live in poverty than Whites or members of other races. Considering the fact that many minority groups who recently migrated to the United States are not living in poverty at the same rates as African-Americans suggests that African- Americans may be dis- criminated against based on preset stereotypes that were popularized during slavery. That is, in order for White slave owners to justify their inhumane treatment of slaves, they dehumanized them. Insisting that slaves were subhuman, Whites were able to justify their maltreatment. It is my belief that lingering racism against African- Americans stems from these preconceptions; consequently, there remains a high degree of covert racism in America with regards to African- Americans. In addition, capitalist nations, such as the U.S., thrive on exploitation. Therefore, one could assume that some group(s) may be prevented from acquiring equality. It is obvious that racism involves complex dynamics, and more research is needed to shed light on this issue, but it is clear that African-Americans are far more likely to live in poverty than Whites or other races. In this study, one of the most troubling findings is the statistical significance of gender and one’s income earning potential. That is, women are far more likely to live in poverty than men, as initially hypothesized. The U.S., from its inception, has been a male dominated society. As such, women are often seen as second class citizens. Thus, women are relegated to positions that are deemed not as desirable as those that are typically occupied by men. These less desirable positions, typically, pay less than the more desirable positions of men. Therefore, we expect to see women INCOME INEQUALITY by Terry Holt 16 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) being more likely to live in poverty than men. Changing attitudes towards women and laws enacted to bring about gender equality would help to ameliorate this problem. The respondent’s highest degree of formal education was also found to have a very significant effect on the probability of living in poverty. As hypothesized, respondents who have attained more formal education are far less likely to live in poverty than those with less education. Respondents who are more educated are generally more valuable to their respective employers because of specialized training and knowledge. Therefore, the more educated person is more likely to a hold higher paying position than a less educated person. As a consequence, the more educated is less likely to live in poverty than the less educated person. Respondents who were raised in the Catholic and Protestant religion were also found to have a significant effect on their income earning potential. That is, people who were raised Catholic or Protestant are far less likely to live in poverty than people who were raised with no religious belief. As hypothe- sized, people who are raised in a strong Christian based belief system are more likely to have a stronger work ethic than those who were raised with no religious belief. Traditional values of Christian based religious belief systems encourage its members to work hard to gain God’s favor. As hypothesized, respondents who were affiliated with the Independent political party were found to be far more likely to live in poverty than people who were affiliated with the Republican party. Independent party members can be seen as those who want to radically change government. Therefore, we would expect them to be ostracized by the powers that be; as a result, Independent Party members might have restricted employment opportunities. The independent variables in this model that were not found to be statistically significant at the .05 level are as follows: other race, age, Jewish, other religion, and other political party. Respondents who are African- American and women continue to be the prime victims of inequality, which presents significant barriers for them and can be the catalyst for impoverished life opportunities. Sadly, many Blacks and women are still plagued by apparent discrimination; consequently, these groups are often mired in poverty, deprivation, and despair. Racism, no doubt, involves a complex set of factors that are beyond the scope of this study. For example, some factors that were not considered in this study that may contribute to lingering racism in America are reduced federal funding of social programs, economic factors, cultural, and psychological damage that past racial discrimination has inflicted on minorities, especially African- Americans. Thus, while this study does support my initial hypothesis that ethnic discrimination remains a central hind- rance to the equality of opportunities for many in the United States, the subject of discrimination needs further investi- gation. INCOME INEQUALITY by Terry Holt 17 CALIFORNIA SOCIOLOGY JOURNAL, 2010, VOL. 2 (ISSUE 1: 1-17) REFERENCES Allport, Gordon. 1991. “The Nature of Prejudice” Political Psychology 12(1):125-157. Sears, David O. 1995. “The Scar of Race.” American Journal of Sociology. 100(5)1351-1354 Sears, David O., and P.J. 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