Sociation Today®
ISSN 1542-6300
The Official Journal of the
North Carolina Sociological
Association
A Peer-Reviewed
Refereed Web-Based
Publication
Volume 15, Issue 1
Spring/Summer 2017
| Identifying
Barriers to Economic
Self-Sufficiency:
A Study of Women in Western North Carolina* by Cameron Lippard Appalachian State University and Elizabeth Thomas Tulane University Introduction
Historically,
women in the United States have faced
higher levels of economic hardship than
men. According to the U.S. Census
(2010), poverty levels among women ages
18 to 64 in the U.S. are higher than
men, with 15.5 percent of women in
poverty compared to 11.8 percent of men.
In 2011, women earned approximately 80
cents to every dollar a man earned
(National Committee on Pay Equity 2013).
On a local level, this story is the
same. In the "High Country" (Ashe,
Avery, and Watauga counties) of North
Carolina, poverty levels for women
eighteen years of age and older are 15.6
percent, 17.5 percent, and 20.9 percent,
respectively (US Census 2010).
Scholars have argued that women face significant economic disadvantages, many of which can be linked to the "feminization of poverty". This phenomena states that women face significant barriers to becoming economically self-sufficient or independent (Pressman 2003). These impediments include low educational attainments and incomes, lack of familial support, number of children in the household, as well as lack of access to stable employment, affordable housing, and good health care (Edin 1995). After being approached by local agencies to develop an assessment of women's economic issues in the area, this research-based community project focused on the following research question: what are the barriers to economic self-sufficiency for women living in the High Country? We defined economic self-sufficiency as the ability of individuals or families to meet their needs with minimal or no financial assistance from private or public organizations (Pearce 2012). Variables used to construct our measurement of economic self-sufficiency included employment stability, housing, educational achievements, number of financial dependents, affordable health care, reliable child care, permanent transportation, disability status, self-esteem, and relationship status. For the purpose of this research, both quantitative and qualitative data were utilized. First, we used surveys to collect economic and demographic data from women living in Ashe, Avery, and Watauga counties. Second, we conducted two focus groups that allowed respondents to express their views about the barriers they believed to be restricting them from becoming economically independent. Our sample included 103 women who lived in Ashe, Avery, and Watauga counties, although the majority was from Watauga County, North Carolina. Results of this project reflected the fact that economic self-sufficiency is a complex issue and goal. First, we found that no women in our sample had complete economic independence. Second, the data collected suggested four influential barriers to economic self-sufficiency including reliable transportation, affordable housing, access to mental health care, and higher self-esteem. While respondents believed that these four barriers had the greatest impact on their economic self-sufficiency, focus group results suggested many such factors work in tandem to restrain women from reaching economic independence.
Context Matters:
Economic Insecurity in the High Country
Economic opportunities for any resident
in western North Carolina are
constrained foremost by historically
persistent economic insecurity.
Residents in the counties under
investigation (Ashe, Avery, and Watauga)
reside in southern Appalachia or the
"High Country" of North Carolina, which
has been economically struggled for
decades. This area has struggled with
providing enough employment
opportunities, strong wages to combat
high costs of living, adequate
affordable housing, and transportation
systems due to extremely variable costs
of living (Black et al., 2007). The
Appalachian Regional Commission (2013)
identified all three counties in this
study as either economically "at-risk"
or "transitional" for having some of the
worst unemployment rates, per capita
market incomes, and poverty rates in the
United States.
Some of this economic insecurity is due to few job opportunities that offer a wage comparable to the cost of living or living income standard. For example, less than 22 percent of the available jobs in the identified counties pay over the current minimum wage of $7.25 an hour (NC Division of Employment Security 2013). Of those available positions that paid more than minimum wage, less than five percent provide an income that could support a family of four. The living income standards recently calculated for the area require a wage of at least $23 an hour to support this type of family (Sirota and McLenaghan 2010). In 2010, researchers developed a "Living Income Standard" (LIS) for North Carolina, which utilized market prices for seven necessary expenses to calculate a more precise measurement of wages needed to live across the 100 counties of North Carolina (Sirota and McLenaghan 2010). These seven expenses included housing, food, childcare, health care, transportation, other necessities and taxes in relation to each city or county in the state. In the past, the Federal Poverty Level (FPL) has been used as the standard for gauging poverty levels in a given region. However, the FPL has not been adequate in explaining why some families which were above the "poverty threshold" still struggled to make ends meet. One of the reasons for this is that the FPL was largely based on food costs and assumed that food consumes one-third of a family's expenses; today, food accounts for a much smaller portion of annual earnings (Sirota and McLenaghan 2010). In addition, the FPL incorporated predetermined living costs within their model, although housing costs varied largely by geographic location. The LIS study produced figures that suggested that most families with two adults and two children living in North Carolina needed to earn at least $23.47 per hour, which is 221 percent higher than the federal poverty level and 324 percent higher than the minimum wage. The results also suggested that women, African-Americans, Hispanics, and immigrants were disproportionately more likely to live in families which fell below the LIS measurement (Sirota and McLenaghan 2010). In addition to this, 60 percent of the adults in those families were employed full-time while still falling short of the NC Living Income Standard within the three counties we examined. For a two-person family (one adult and one child) annual LIS income levels in Ashe, Avery, and Watauga counties should have been $32,657, $34,704, and $37,739, respectively (Sirota and McLenaghan 2010). In a five-person family (two adults and three children), the annual LIS budget for three counties should have been $56,442, $56,834, and $60,040. These income levels were double or triple the actual income levels reported by the U.S. Census in 2010 (see Table 1 below). In addition, based on the LIS measurement, wages in all three counties needed to be about 200 percent more than reported, regardless of family size. While average wages in these counties rested around $10 an hour, costs of housing, food, childcare, and other measured items required an average wage of $23 an hour. In short, over 65 percent of families in these counties had incomes that were much less than what was necessary to economically survive, regardless of family size or composition. The labor market is problematic and unreliable in these areas. When looking at available jobs in today's market, only two percent of jobs that paid an income which was suitable to address the living income standard suggested above required at least a post-graduate education (i.e., Ph.D., J.D.) and/or five to eight years of experience (NC Division of Employment Security 2013). As suggested by the skills mismatch hypothesis (Handel 2003), the education and skills of the labor pool in western North Carolina may not match the needed qualifications for those jobs which pay more, particularly since only about six percent of these counties' populations have a professional or post-graduate degree. In 2013, the labor market and job opportunities came from three industries or sectors of employment in the area: government-public, retail, and service sectors (NC Division of Employment Security 2013). Appalachian State University, a public university enrolling 16,000 students and hiring over 3,700 people was the largest employer of the three counties. The next largest employers were other North Carolina government services, including the Department of Transportation and Social Services. As for retail, most jobs rested in part-time work in fast food restaurants and shopping. However, one of the largest industries that provided employment was the service or "tourist" industry in the area. Specifically, the Appalachian Regional Commission (2007) report noted that tourism has become the biggest non-government industry in central and southern Appalachia. This is true for western North Carolina where outdoor activities (camping, skiing, and hiking), the Blue Ridge Parkway, fall festivals, and blue grass music bring millions of tourists to the "High Country." In 2012, tourism to Watauga County generated over $210 million (NC Division of Tourism 2013). However, over 64 percent of the employment opportunities offered by this industry are part-time, seasonal work with just above average wages ($8.25 an hour) (NC Division of Employment Security 2013). Overall, the labor markets in 2013 do little to provide economic opportunities for many individuals and families to escape the poverty that has plagued this area. Economic Realities for Women in the High Country
Women's economic situations in Ashe,
Avery, and Watauga County are bleak. For
example, Table 1 below presents median
household income, cost of living,
unemployment rate, relationship status,
labor force participation rate,
education level, home ownership rate
from 2007-2011, and the poverty rate for
all individuals in the three counties.
Since the research question focused on
barriers for women in the high country,
Table 2 also presents the variables
subdivided by sex (female and male).
Statistical information representing
"females only" is not available for
every variable, therefore, Table 2
contains a smaller amount of variables
than Table 1.
Table 1: Characteristics
of Population U.s. and the High Country
Table
2:
High Country
Characteristics (women
and Men Comparisons over
Each County)
According to the US Census (2010),
the median household earnings for
full-time employed women in the
mountain counties of Ashe, Avery
and Watauga were $27,713, $28,371
and $31,885, respectively. In each
of these counties, incomes for men
were higher than incomes for
women. On average, men in
Ashe and Avery counties made an
estimated $5,500 more per year
while men in Watauga County made
$6,200 more than full time
employed women (US Census, 2010).
The cost of living in each county differed by family composition, number of children, and geographic location. For the purposes of this study, the estimates for a household with two adults and two children were used in Table 1. The variables compiled in the estimate include housing, childcare, transportation, food, health care, and other necessities in respect to each county examined. Labor force participation was represented for all individuals in each presented county and not specifically by sex. For all three counties, a range of 50 to 60 percent of the total population was employed. Thirty-five to fifty percent of the total population within each county was considered unemployed. Poverty levels for each county revealed similar trends when comparing two-adult households to single, female-headed households. Less than ten percent of two-adult households lived below the poverty level within each of the three counties. In comparison, thirty-six to forty-three percent of households that were female-headed with no spouse present lived below the poverty level. An even more drastic comparison was evident between female-headed households and female-headed household that have related children under five years old. Seventy-three to ninety-three percent of female-headed households with related children under five years old lived below the poverty level in Ashe, Avery, and Watauga counties. The Feminization
of Poverty and Continuing
Barriers
As first identified by Pearce
(1978), the "feminization of
poverty" thesis noted that women
faced higher levels of poverty
than men in the United States
because of a wage gap and
increasing female-headed
households with children (see also
Bianchi 1999; McLanahan, Sørenson,
and Watson 1989; Peterson 1987;
Pressman 2003; Reskin and Padavic
2002; Thibos, Lavin-Loucks and
Martin 2007) Although some
researchers have suggested that
there have been significant
improvements in economic
conditions since the 1970s for
American women (see Bianchi 1999),
there are still a number of
factors that complicate the
possibilities of women becoming
economically independent. A review
of current research focusing on
women's poor economic conditions
suggests six main barriers to
economic stability: education,
income or wage levels, children
and single parent households,
family ties, affordable housing,
and affordable and accessible
health care.
Education and the Wage Gap
According to the U.S. Census
Bureau's 2010 findings, women 25
and older were more likely than
men of the same age to have
completed at least high school and
earned a college degree (Crissey
et al. 2013). Human capital
theory implies that investment in
health, job training and education
promises higher future market
returns. This theory shows that
education not only improves math,
verbal, and cognitive skills but
also contributes to one's values,
behaviors, and attitudes (Pandey
et al. 2006, 2008).
Commonly, employees with more
years of education are more sought
after and given higher salaries
and benefits. Thus, the higher
level of education one completes
should result in a higher level of
economic self-sufficiency.
Despite advances in educational attainment for women, some studies have shown that women's views on whether they see themselves as economically self-sufficient were unrelated to their employment status, income levels, job history, education, race, age, or family size (Gowdy and Peralmutter 1993). Research has also shown that less than 10 percent of mothers with a bachelor's degree live below the poverty line, compared to over 50 percent for those without a high school diploma (Pandey et al. 2006). Poverty among married women without a high school degree was 20 percent above their counterparts who had bachelor's degrees. Women without postsecondary education worked jobs that paid lower wages and provided fewer services than they received when on welfare (Pandey et al. 2006). Interesting to note, the odds of living above the poverty line for single mothers with some college is three times those with a bachelor's degree and nine times the odds for those without a high school degree. Also, educated women tend to marry educated men, and upon divorce or becoming widows, they tend to receive more financial resources from their marriage in the form of child support, alimony and assets compared to their less educated counterparts (Pandey et al. 2006, 2008). As stated earlier, more women are receiving bachelor's degrees than men but the amount of low-income women and single mothers going to college has declined since the 1996 welfare reform and the later 2005 Deficit Reduction Act (Pandey et al. 2008). With continued emphasis on welfare to work, more women have been in need of their four-year degree to secure jobs which provided economic security. This has shown that educational status continues to be positively related to economic status with both married and single mothers (Pandey et al. 2006). Across the board, women continue to have lower wages than men. As of 2013, women on average make 80 cents to every dollar a man makes. Reskin and Padavic (1994) have argued that these wage differences have been due to a number of factors. First, there is a "sexual division of labor" which tracks women into "pink collar" occupations that offer low wages and require less skill than other occupations. Tasks such as working with children or customers are thought to be appropriate to women's gender roles, which are given a lower status and are thus, paid less. These jobs also typically reflect the work that women perform in the home, such as cleaning and cooking. This traps women in poverty because the kind of jobs they can get do not pay well; thereby making it nearly impossible for them to rise out of poverty. The gender roles that our society enforces also contribute to the feminization of poverty. Men are socialized to be competitive, rational, and dominating, all of which are characteristics valued by a capitalistic society. Women are seen as irrational and emotional, which allows for capitalists to look down on women and make them dependent on men (Hartmann 1984). These gender roles also support the gender ideology of Western society's culture. Western society tends to believe that women are supposed to be dependent on men, that women have fewer needs than men, and that women's work is not as valuable as men's (Reskin and Padavic 2002). Second, the discrepancy that we see in wages between men and women is also due to the "glass ceiling" that curbs many women's careers. By definition, the glass ceiling consists of obstacles that women face along the journey to gaining a higher position in an organization or career (Abercrombie, Hill, and Turner 2006). This is accomplished in both covert and overt ways. For example, because the majority of managers within organizations are male, females may not be as connected with their social networks and therefore, have less of a chance at making an impression for possible advancement. It is also common for people to hire others whom they are comfortable working with. Men may be more comfortable working with other men, instead of women, which would subconsciously influence a male manager's decision when promoting new managers (Abercrombie et al. 2006). Due to these restrictions impacting women, no matter how hard they work or achieve set-out goals in their jobs, they are overcome by men blocking their access to higher positions that offer better pay. Finally, while women and men find themselves in very different occupations, being paid very different wages, economic forces are strong predictors of opening and closing job opportunities, both nationally and locally. Williams (1992) argued that while women do face pay- and advance-issues in most occupations, some occupations arise over time that advance women and skirt around gender issues of wage inequalities. For example, by the 1970s jobs in manufacturing, which were traditionally the best-paying option for low income, unskilled, and uneducated women, have been moved overseas to developing countries that have less governmental regulation. Therefore, this relocation of manufacturing and industry type jobs for women has forced them into service industries, teaching, and various other occupations that pay at or slightly above the legal minimum wage (McCall 2000). However, as Bianchi (1999) points out, there are some occupations in which women have earned good wages in comparison to men, such as nursing, due to the demands of the health industry. But, again this profession is largely woman-dominated, and even when men enter it, they are often pushed into administrative positions quickly, a concept referred to as the "glass escalator" (Reskin and Padavic 2002; Williams 1992). In short, researchers have to look at local labor market context as well as macro-level economic shifts to better understand women and the wage gaps they face. Female-Headed Households with Children
As noted first by Pearce (1978),
the increase in female-headed
households has increased levels of
poverty for women (see also
McLanahan et al. 1989; Edin 1995).
In 2009, while women accounted for
59 percent of the American
workforce, female-headed
households also represented 25
percent of all families with
children (U.S. Census 2010). Women
who are single parents face a
paradox. As Edin (1995) suggests,
society pushes women to be the
primary caregivers but they cannot
earn enough money to support their
children. In addition, if they
cannot obtain a job that pays a
living wage, then these single
mothers will often turn to the
American welfare system for help
with paying bills and providing
sufficient care for their children
(Edin 1995).
Continuing this paradox is the fact that research finds that child care and lack of child support are two large barriers to economic self-sufficiency for single mothers, beyond wage disparities. Research shows that more policies implementing child care and short-term leaves would correlate with a decrease in poverty among single mothers (Misra, Moller, and Budig 2007). In addition, evidence suggests that within rural areas, mothers will face challenges in finding affordable and reliable childcare (Simmons, Dolan, and Braun 2007). Watauga County is considered a rural area and this challenge is evident in its female population. Childcare, healthcare, and housing account for 60 percent of a family's monthly expenses, with childcare being the single largest expense (Quinterno, Gray, and Schofield 2008). The monthly living income standard budget for childcare is around $411 a month, for a four-person family, in non-metropolitan areas. Childcare usually comes out to one quarter of a family's monthly spending (Quinterno et al. 2008). Childcare can cause significant financial stress, particularly when more than one child is in the household, as well as single mothers do not get the child support they need and that this can cause them to rely on the welfare system (Edin 1995). Many single mothers rely on welfare simply because they cannot afford childcare (Edin 1995). Thus, childcare and its affordability further compounds the economic problem women face in America. Housing and Health Care
One obstacle that poor families
face in Appalachia is the lack of
affordable housing. This is
especially true in areas with high
job growth (Mather 2004). It seems
that people who rent their home
rather than own their home have
higher burdens in regards to
housing. This is usually due to
renters typically having a lower
income than people who own their
home (Mather 2004). In Watauga
County, it is particularly
difficult to find affordable
housing. Because of the
university in Boone, the lack of
affordable housing, and tourism in
the area, it is extremely hard to
live affordably in Watauga County
(Jenkins 2008). When looking at
women who do receive housing
assistance and those who do not,
we find that women who do receive
housing assistance are no more
likely to encounter barriers to
employment and self-sufficiency
than unassisted women (Corcoran
and Heflin 2003). Therefore, there
is a weak relationship between
housing assistance and work
outcomes (Corcoran and Heflin
2003). Research shows that when
measuring housing quality based on
the key aspects of plumbing
adequacy, vacancy rates, home
values, and access to vehicles and
telephones, Appalachia continues
to fall behind the rest of the
United States (Mather 2004).
One of the most financially crippling hurdles to self-sufficiency women face today is the barrier to accessible and affordable health care, both for themselves, as for any other dependents they support. Whether their inability to maintain steady care is due to rising medical costs, lack of health insurance, or other reasons, women are directly affected by their health concerns (Roxburgh 2009; Samuel et al. 2012). Being able to hold down a steady job requires a greater sense of physical well-being and can even be directly related to whether or not one has a common cold (Geronimus et al, 2006; Kaplan 2005; Leukefeld 2012). Through recent changes to our nation's health care laws, females have a wider set of options. Alterations such as the ban on annual and lifetime limits on benefits, the disappearance of co-pays for preventative screenings (i.e. pap smears and mammograms), and well-child visits allow individuals to get the maximum coverage out of their health policies without being denied services or worrying about costs (NCSL 2013). However, Americans have yet to learn about how these benefits work and will still cost individuals significant amounts for health services that are not covered. Although options for the uninsured and unemployed are growing, the rising costs of plausible policies for them often prevents their attainment. In recent studies performed in 2011, the average health care costs of a family of four soared upwards of $16,000, with the family paying nearly $5,000, on average, of that out of pocket. For an individual, however, insurance coverage was estimated at $5,614 requiring nearly $1,000 of that to be paid by the individual (NCSL 2013). With no sign of a decrease in costs, it is apparent why women often suffer at the hands of their own health and struggle to find affordable options to care for their children. Family Ties
A final obstacle facing women and
their inability to refer to
themselves as economically
self-sufficient is the concept of
family ties. In recent years,
studies have been conducted
targeting the idea of two income
families. Many women are often
looked down upon for being single
mothers, or merely women without a
partner; however, as Warren and
Tyagi (2003) have discovered, they
may be the ones with the
advantage. A large part of our
society has been lead to believe
that a combined two-person income
will resolve bills or debts and
provide other types of support
that sometimes comes at an expense
(Misra et al. 2007).
Sudden loss of a job, the appearance of serious medical problems, and divorce are three of the highest indicators for bankruptcy; however, the presence of children is one of the leading predictors of the financial suicide of women (Warren and Tyagi 2003). Once considered a benefit of family life, women are increasingly considering not having children, or at least fewer of them. Sociologists have supported the idea that a lack of children paired with having a wage earning partner had a significant and positive impact on the economic self-sufficiency spectrum (Edin 1995; Simmons et al. 2007; Warren and Tyagi 2003).
Methods
To examine the barriers to
economic self-sufficiency of the
women in the "High Country,"
specifically in Ashe, Avery and
Watauga counties, we drew upon
quantitative and qualitative data
collected from a community-campus
partnership conducted between
January and May of 2013. Our
partnership included local
agencies aimed at providing
services for women and children
throughout our target population
who face economic deficiencies. As
a research team, our goal was to
further the agencies'
understandings of the local women
by asking questions about their
social demographics, their
educational history, and their
opinions about the adequacy of
services provided to them in these
three counties. Throughout this
partnership we conducted several
planning meetings, and decided to
use a mixed-method approach
relying on surveys and focus
groups. We, as well as the
community partner, felt that these
methods were the best way for
subjects to voice their thoughts
and opinions on the issue,
particularly since the agency
partners noted issues with
literacy.
Initially, with the help of the community partner, we designed a thirty-question survey that was distributed to the participating agencies including closed and open-ended questions crafted by our research team and participating agencies. Included within the survey were questions regarding age, relationship status, employment, housing, education attainment and income; we also inquired about the current utilization of medical services and various agencies or programs being used by the participants throughout the counties (available by request). Upon completion of the survey, it was submitted for review with the participating agencies and approved for use. We considered the potential literacy issues and decided that the survey could be administered three ways: in person by a research assistant, online through a secure server offered by the university, or self-administered in hard copy form. We asked all participants for no identifying information to make it anonymous to us, as well as the partnering agency. Once a week, members of the research group visited the agencies to conduct and collect completed copies of the survey. The total number of surveys collected was 103. Beyond the surveys, two separate focus groups were conducted to allow participants to express in-depth views on the barriers they face and how those are associated with achieving economic self-sufficiency. Each focus group involved eight to ten participants who were residents of Avery and Watauga Counties, totaling 19 participants. Three to four female facilitators were present during each focus group, and each focus group lasted approximately sixty to ninety minutes. The focus groups were also digitally recorded for further data analysis. All research members were trained and certified through the Institutional Review Board at the corresponding university, as well as trained on various data collection methods throughout the research process. All participants were assured they would receive total anonymity and confidentiality during the survey process, as well as their participation in the focus groups, by not attaching names or identifying information to their responses. Furthermore, it was also made clear to all individuals that by volunteering for this research their participation could potentially lead to more funding to further aid women in future, similar situations. Following the research, all quantitative data was cataloged into the statistical software package SPSS. All qualitative coding was performed through qualitative content analysis of the survey results. Descriptive as well as inferential statistics were used to further analyze our data and shape it into a more understandable and relatable data bank. Three types of analysis were conducted to describe the data; descriptive, bivariate, and multivariate analysis. First, when conducting the descriptive analysis, the data was entered into SPSS, and by looking at the percentages of comparative variables, a descriptive explanation was created to examine the most important barriers to economic self-sufficiency. Second, a bivariate analysis was conducted in order to compare the independent variables and to create an economic sufficiency variable based on several barrier indicators (see results section). Finally, these indicators were combined into an overall score that categorized the respondents into 4 categories (see results section) and gave them an economic self-sufficiency score between 0 and 100.
Results
This study focuses on three
counties that are part of what is
defined as "The High Country." The
counties included are Ashe, Avery
and primarily Watauga. The
majority of the respondents (84
percent) resided in Watauga County
with Avery County being the
second-most represented at 11
percent. For the overall sample,
respondents' ages ranged from 18
to 80 with a mean of 40 years old.
The most common age range of 19 –
30 years old described 27.2
percent of the sample. The sample
was 97% white with only three
respondents identifying as Black
or African American. Of the
respondents, only 35 percent were
married and another 25 percent
were single. However, it should be
noted that around 13 percent were
in at least a "steady
relationship." Majority of women
had children, with most having
between one and three children. As
for education, only a few had less
than a high school diploma and
about 21 percent had some college
education but had not completed a
degree.
One important finding was that nearly half (49.5 percent) of the women were unemployed. This is later reflected when most women state that the largest barrier for them was stable employment (see discussion). The monthly income for our study ranged from $0 per month to $4600, although the high income earners were certainly outliers since the mean and median income was $985.65 and $730 per month, respectively. Housing costs ranged from $0 and $1800 per month with an average of cost at $601.13 per month. Most of the women in our study owned their own vehicle (61.2 percent), but a large number still used public transportation (21.4 percent). Most women rented their housing (41.7 percent) while 30.1 percent owned. This left a large percentage (27.2 percent) of women to be either homeless or using agency provided housing. Table
3:
SAMPLE DEMOGRAPHICS (N =
103)
Economic
Self-Sufficiency
Measurement (ESS)
The measurement of
self-sufficiency was a
required element that the
partnering agency wanted
to produce to be able to
share with other agencies
working with women. Based
on the literature reviewed
above and conversations
with the partnering
agency, we created this
economic self-sufficiency
index (ESS) in which we
assigned a point value to
each response option where
the most possible points
earned by any respondent
was one hundred; one
hundred signifying the
highest level of
self-sufficiency where all
basic needs were met and
zero indicated a complete
lack of economic
self-sufficiency. Two of
the questions were based
on a twenty-point scale
measuring the respondents'
personal perception of
their level of ESS due to
its prominence in the
literature on
self-sufficiency and the
agency's insistence that
these represented
important cues of
self-reliance and economic
stability due to their
experiences (see Table 4).
The remaining six received
a total of ten points
each. The questions about
financial stability and
being able to pay one's
bills were given a higher
point scale because these
questions addressed
women's perceptions of
ESS, which we found to be
pertinent to their actual
achievement of ESS. The
six other questions were
also important but did not
address women's personal
perception of ESS, thus
these questions were given
a lower point scale, where
ten was the maximum. Using
statistical processing
software we added the sums
of these freshly-coded
variables and arrived at
our new ESS measurement.
The scores can be further divided into four categories. These definitions capture the majority of respondents in each category but there is some overlap (see Table 4): Safe (76 - 100 pts): Most or all basic needs met. Sufficient income and/or subsidies to take care of bills and any other needs are well met by community services. Although these women have a stable income, they do not have enough savings to cover 3 months of expenses. At Risk (51 - 75 pts): Most have all but one or two needs met. Some might need more reliable transportation or childcare or they sometimes must use more services to cover gaps in an unreliable job. Because of this they sometimes struggle to pay their bills. Struggling (26 - 50 pts): Women in this category have either many small problems, such as no health insurance or unreliable childcare, or one large problem, such as major health complications or homelessness. They are heavily reliant on community and federal services, which often don't fully satisfy their needs. Their income is not sufficient and they often cannot pay their bills. Crisis (0 - 25 pts): Women in this category have multiple, significant problems and they are often unemployed and homeless, sometimes with children. They are almost completely reliant on federal and community services and can never pay all of their bills. Many times children compound these issues. Table
4:
ESS Score matrix
The scores of respondents in this
survey ranged from six to ninety
posing a wide representation of
what each individual's score
indicated. Out of 87 respondents,
19.5 percent fell into the lowest
category of 25 points or less (see
Figure 2). These women were more
likely to have one or more
children and face challenges
acquiring secure living
arrangements. Bills for these
individuals far outweigh their
income levels and personal needs
are rarely met, if at all.
Respondents who fall into this
category are considered to be "in
crisis" with a tendency to have
all basic needs unmet and in need
of immediate assistance.
The two
largest categories were "struggling"
and "at risk", with 36.8 percent and
39.1 percent, respectively. These
categories captured a wide range of
situations, ranging from relatively
stable, to on the verge of crisis.
All of these women were heavily
relying on services to stay afloat
although some used many more
services than others. Only 4.6
percent of respondents in our study
scored above a 75, representing the
"safe" category. A score this high
suggests that these individuals are
minimally challenged by a lack of
income and their basic needs are
sufficiently met through a
combination of some community agency
assistance, but primarily
self-reliance. While these women are
more likely to have a stronger sense
of stability in their levels of
self-sufficiency, they still do not
represent the ability to cover three
or more months of expenses should
their income disappear or economic
crisis strike.
Most Common
Barriers
By giving
a list of possible barriers for
the respondents to choose from, we
allowed them to define how their
economic self-sufficiency is being
impeded. Figure 3 below depicts
the top five barriers chosen by
respondents; it should be noted
they could pick all that applied
to their situations.
The final question in the survey
also asked respondents to select
the barrier that has the greatest
impact on their economic
self-sufficiency. As indicated in
Figure 4, 34 percent of the
respondents agreed that stable
employment is the number one
barrier to their economic
self-sufficiency. However, what
the research will suggest is that
other barriers such as
transportation and affordable
housing are going to weigh more on
their economic self-sufficiency.
After creating an economic
self-sufficiency model, we ran
a bivariate analysis of what
our respondents defined as the
most detrimental barriers to
their ESS. Despite the
barriers our female
participants proposed to be
the most influential on their
achieving economic
self-sufficiency, our model
has shown that reliable
transportation, affordable
housing, access to mental
health care, and self-esteem
are the top four most
influential barriers. In the
analysis below, we use the
signifier of (r = x) to denote
the strength of each barrier.
This equation also shows that
the relationship of each
barrier to economic
self-sufficiency is that of a
negative one. This implies
that the more often women
report needing services for
these top four barriers, the
less economically
self-sufficient they are.
Therefore, we can infer that
the lower the value in our (r
= x) equation, the more this
barrier impedes the economic
self-sufficiency of our
respondents.
Reliable transportation was shown to be the number one barrier (r = -.594*) against achieving economic self-sufficiency among the women utilizing services from our organizations. During the first focus group, some women commented on unreliable transportation being a problem for them. When specifically referring to the AppalCart in Boone (a free public transportation system that runs throughout Boone, NC), they stated that it was very helpful that the AppalCart is a free service, but that when certain routes are restricted or simply do not run certain days and times, it is very inconvenient for individuals who rely on that transportation for their job. Our model showed that affordable housing was the second most influential barrier (r = -.470*) to these women becoming economically self-sufficient. During the second focus group, one participant stated, "The town of Boone takes advantage of HUD (Housing and Urban Development) like you would not believe. $850 for a trailer with two bedrooms? Come on now!" These participants also attributed the high cost of living to college students driving the rent up, stating that students have to live in Boone and will pay whatever they need to for a place to stay during school. Another participant stated, "HUD is the only reason that most people can even make it". According to these participants, affordable housing is almost non-existent in Boone and the only reason they do have a home in most cases is thanks to HUD programs. The third most influential barrier to economic self-sufficiency for the women in our study was shown to be access to mental health care (r = -.434*). During our first focus group, a few participants commented on how, because they no longer qualify for Medicaid, they cannot receive the types of services and/or medications they need to deal with their mental illnesses. One participant stated, "I have Post Traumatic Stress Syndrome. I'm supposed to take medicine but I can't afford it because I don't have Medicaid. I know I need counseling and I know I need to talk to someone, but I can't afford that". Another participant stated that she is chronically depressed and manic, which affects her sleeping habits. Those mental illnesses combined with her tragic life experiences (beaten by her parents at a young age) hinder her ability to get a full night's rest. Although she used to take sleeping medicine to help deal with this, she can no longer afford it because she was stripped of her Medicaid. Access to mental health care would be extremely beneficial to these two participants in particular, but also to our target population as a whole, as mental health leads to physical health. The fourth most influential barrier to economic self-sufficiency, as shown by our equation, is that of self-esteem (r = -.421*). Throughout our first focus group, the participants consistently brought up how self-esteem is a large barrier to their economic self-sufficiency. One participant, when discussing her experience trying to apply for Medicaid, stated, "Don't you love the way they talk down to you? I'm a strong woman and I left out of there in tears. I felt like I was garbage". Another participant added, "It's the way that they talk to you, like [you're not] good enough, [you're not] doing something right". Yet another participant added, "I should just give up. No one else has faith in me, so why should I have faith in myself?" Clearly, the issue of self-esteem penetrates a variety of aspects in the lives of these women and affects their ability to receive some of the necessary services they seek out. Most Influential Barrier
After analyzing the data
collected through the surveys,
the independent variables were
chosen to test the most
significant barrier women face
in the "high country" in
regards to becoming
economically self-sufficient.
An OLS regression model was
used to determine significant
relationships between the
independent variables chosen
and the dependent variable,
which was the ESS score. The
independent variables included
were: age, relationship
status, housing, whether the
participant lived alone or
with others, whether the
participant lived inside or
outside city limits, number of
children, how many children
the participant supports
financially, the use of
financial assistance for
childcare, education level,
employment status, how many
individuals rely on the
participant for financial
support other than children,
income level, transportation,
health insurance, the
participant' s use of the
emergency room for something
that was not an emergency
within the past year, physical
and mental disability status,
and self-esteem.
The results of the regression analysis suggest that while all barriers maintain some level of significance, there is not one specific barrier that keeps women from becoming economically self-sufficient when holding all other independent variables constant. This analysis reveals that there is not a difference in levels of significance among the barriers in predicting economic self-sufficiency. While we ran some interaction variables, none were significant in solely predicting economic self-sufficiency within this sample. Discussion
and Conclusions
For this project, multiple
barriers were identified and
evaluated to assess the impact
they pose on the achievement
of economic self-sufficiency
for women in the High Country.
It is important to note that
of the women who chose to
participate in this study,
none of them met the living
income standard of what is
considered economically
self-sufficient, as reported
by the most recent study by
Sirota and McLenaghan
(2010). The data
indicated that there is a
combination of factors that
impede women from becoming
economically self-sufficient,
though there was little
variance among these barriers;
showing that no one specific
variable keeps women from
attaining financial stability.
However, the data highlighted
four specific barriers that
have the greatest impact on
self-sufficiency including:
reliable transportation,
affordable housing, access to
mental health care, and
self-esteem.
It should also be noted that within the focus group discussions, participants clearly indicated a number of barriers working in tandem to suppress their economic independence. During one of the focus groups which contained seven women who are all Watauga County residents, it was suggested that they would greatly benefit from additional transportation programs, such as "Wheels to Work", which allows those without reliable transportation the opportunity to use a donated car to transport them to their jobs. This type of program is especially efficient when forms of public transportation, such as the AppalCart, are not running or are on limited schedules. One respondent stated, "I can't get to work if the bus don't [sic] run when I need to go to work….5am is just early for a public bus I guess." In addition, several participants lamented that many things have to fall in place in order to make it financially. For example, one participant stated, "This isn't rocket science, you know? You need a good job that gives you decent pay so you can pay the babysitter, or even save up for a better car so you can get to work on time so they want fire you. Dominos!!" Another barrier to women was affordable housing. Because of the university in Boone, the lack of affordable housing, and the overflow of tourism in this area, it is extremely hard to live affordably in Watauga County (Jenkins 2008). As one focus group participant stated, "HUD is the only reason that most people can even make it". According to these participants, affordable housing is almost non-existent in Boone and the only reason they do have a home in many cases is thanks to program such as HUD, which offers homeownership assistance programs. Access to mental health care was portrayed as the third most important barrier for these women. Women are often times more likely to be exposed to repeated stressors, influencing rates of depression, malnourishment or eating disorders, high risk of anxiety, as well as a passel of other mental health concerns, and while options for the uninsured and unemployed are growing, the costs of mental health care are still too great for many women to afford (NCSL 2013). During a focus group discussion, one participant stated, "We all need support. I know the money matters but I need folks to talk to so I can get things off my chest and take it home to my babies." For these women, being able to access mental health services and medications is crucial because it also influences their physical health, job stability, and overall self-esteem. The last major barrier to economic self-sufficiency for these women was that of self-esteem. Certainly, the lack of self-esteem can be related to the levels of education, income, and economic prospects for women in this sample. During the focus groups, women consistently described how their situations chip away at their levels of self-esteem. These women stated that when they try to receive assistance from agencies to better themselves, they feel demoralized by the way they are spoken to and treated, which negatively impacts their self-esteem. The presence of negative stereotypes and stigmatization can contribute to the lack of women pursuing service agencies. As past research has shown, women find themselves at an economic disadvantage. The evident wage discrepancy between men and women has led to women having generally higher levels of poverty; referred to as the feminization of poverty. Moreover, women continue to carry the economic and emotional burden of raising children. Overarching all of these women's problems is the fact that they live in an area that struggles to offer enough jobs and adequate wages to live and thrive. Overall, this research shows that there continues to be a number of variables that explain women's inability to be self-sufficient; however, there is no one variable that seems to best predict economic dependency or independence for women in the region. There are some limitations to the data presented that should be considered and applied with caution. First, this data is regionally specific to the High Country of North Carolina including Ashe, Avery, and Watauga Counties and based mostly on a convenience sample of women who were identified by our partner agencies for participation. Therefore, these women were already receiving some services to help them economically cope, skewing our economic self-sufficiency matrix scores to a more positive result of less women in economic crisis. More important, we did not talk to women who were possibly receiving no services to economically cope, which may provide a very different set of conditions. Second, the data collected did not include a racially or ethnically diverse sample even though the areas have some diversity. The three counties identified has recently seen a 2 to 3 percent increase in the Latino population (Lippard and Price 2011). The economic conditions that Latino women face in this area may be different, particularly since many are first-arrival immigrants to the area who do not know much about available services (Lippard and Price 2011). Future researchers should consider looking at a larger population, possibly a statewide study in order to get more accurate results and full comparisons. Random sampling should also be an integral part in continuing research regarding women's self-sufficiency in the area to ensure diversity. Certainly, it is important for this research to be continued and attempt to include women who are not already receiving services from various public and private agencies. Finally, more focus groups need to be conducted to collect more qualitative data to further explain issues illustrated with this research, particularly the intersectionality of several barriers women continue to face attempting to economically survive in Western North Carolina. However, this research is unique in that it focuses on a specific area of North Carolina, the "High Country", which is similar to other small mountain areas which may be facing similar issues with economic self-sufficiency among women. Being able to understand the unique barriers women in areas like the "High Country" face and understanding how those barriers may differ than barriers in an urban setting is beneficial to investigating targeted solutions. The findings from this study are also interesting because they measure respondents' thoughts about their ESS barriers with what the multivariate regression model equates with ESS barriers for the target population. Discovering that women's perceptions of barriers and model-defined barriers differed, can allow organizations and researchers to address the most influential indicators of economic self-sufficiency. Footnote
*This research
was a collaborative effort
with the Appalachian Women's
Fund of North Carolina and
undergraduate students from a
senior seminar course in the
Department of Sociology at
Appalachian State University.
We would like to especially
recognize the following
student contributions by
listing their names: Christine
Beatty, Kendra Black, Lew
Cabral, Katherine Caswell,
Alexander Dale, Hope Dearman,
Lisa Hall, Natalie Harkey,
Katelyn Latino, Nicholas
Logel, Hannah Lowman, Brian
Okam, and Cory Sommer.
Referemces
Abercrombie,
Nicholas, Stephen Hill, and
Bryan Turner. 2006.
Dictionary of Sociology.
London: Penguin Books.Access NC: Ashe County 2013a. Commerce Economic Development. (http://accessnc.commerce.state.nc.us/docs/ countyProfile/NC/37009.pdf) Access NC: Avery County 2013b. Commerce Economic Development. (http://accessnc.commerce.state.nc.us/docs/ countyProfile/NC/37011.pdf) Access NC: Watauga County 2013c. Commerce Economic Development. (http://accessnc.commerce.state.nc.us/ docs/countyProfile/NC/37189.pdf) Appalachian Regional Commission (ARC). 2013. "County Economic Status in Appalachia, FY 2013." Retrieved June 3, 2013. (http://www.arc.gov/research/ MapsofAppalachia .asp?MAP_ID=64)nc. Appalachian Regional Commission. (ARC). 2007. "Sources of Regional Growth in Non-Metro Appalachia." Retrieved April 1, 2013. (http://www.arc.gov/r esearch researchreportdetails.asp?REPORT_ID=84). Black, D.A., M. Mather, and S.G. Sanders. 2007. Standards of Living in Appalachia, 1960 to 2000. Retrieved February 3, 2013 (http://www.arc.gov/assets/research_reports /StandardsofLivinginAppalachia). Bianchi, Suzanne M. 1999. "Feminization and Juvenilization of Poverty: Trends, Relative Risks, Causes, and Consequences." Annual Review of Sociology 25: 207-33. Budlender, Debbie. 2005. "Women and Poverty." Agenda (64): 30-60. Crissey, Sarah R., Nicole Scanniello, and Hyon B. Shin. 2013. "The Gender Gap in EducationalAttainment: Variation by Age, Race, Ethnicity, and Nativity in the United States." Housing and Economic Statistics Division, U.S. Census Bureau. Retrieved January 13, 2014. (http://www.census.gov/hhes/socdemo/education/data/acs/CrisseyScannielloShin _poster.pdf). Community Economic Toolbox 2011. "Labor Force: Avery County, NC." Retrieved April 1,2013 (http://economictoolbox.mit.edu/labor_force.php?region_id= 1&sfips=37&cfips=37011&rurality_flag=0&sfips1=39&cfips1= 39119&return_page=education.php). Community Economic Toolbox 2010a. "Labor Force: Ashe County, NC." Retrieved April 1, 2013 (http://economictoolbox.mit.edu /labor_force.php?region_id= 1&sfips=37&cfips= 37009&rurality_flag=0&sfips1=29&cfips1=29185& return_page=education.php). Community Economic Toolbox 2010b. "Labor Force: Watauga County, NC." Retrieved April 1,2013. (http://economictoolbox.mit.edu/labor_force.php ?region _id=1&sfips=37&cfips=37189&rurality_flag =0&sfips1=00&cfips1=00000&return_page=historical.php). Corcoran, Mary and Colleen Heflin. 2003. "Barriers to Work Among Recipients of Housing Assistance." City Scape Housing Assistance and Welfare Reform 6(2):73-87. Edin, Kathryn J. 1995. "The Myths of Dependence and Self-Sufficiency: Women Welfare, and Low-Wage Work." Focus 17(2):1-9. Geronimus, Arline T., Margaret Hicken, Danya Keene, and John Bound. 2006. "Weathering" and Age Patterns of Allostatic Load Scores Among Blacks and Whites in the United States." American Journal of Public Health 96(5): 826-833. Gowdy, Elizabeth A. and Sue Peralmutter. 1993. "Economic Self-Sufficiency: It's Not Just Money." Affili 93(8):368-387. Handelman, Michael J. 2003. "Skills Mismatch in the Labor Market." Annual Review of Sociology 29:135-65. Hartmann, Heidi. 1984. "The Unhappy Marriage of Marxism and Feminism: Towards a More Progressive Union." Capital and Class 3(2): 1-33. Jenkins, Carl D. 2008. "Appalachian Rural Homelessness: The Case of Watauga County, North Carolina." Masters of Arts Dissertation, Department of Appalachian Studies, Appalachian State University. Kaplan, George A. Siefert., Kristine Ranjit, Nalini Raghunathan, Trivellore E.Young, Elizabeth A.Tran, Diem Danziger, Sandra Hudson, Susan Lynch, John W.Tolman, and Richard Tolman. 2005. "The Health of Poor Women Under Welfare Reform." American Journal of Public Health 95(7): 1252-1258. Lippard, Cameron D. and Jammie Price. 2011. "Latino Health Care in Southern Appalachia: A Community-Engaged Examination." Journal of Applied Social Science, 5(2): 66-87. Leukefeld, Sarabeth. 2012. "Human Capital, Mental Health, Substance Use and Social Support Among Low-Income Women." PhD Dissertation, College of Social Work, University of Education, Kentucky. Mather, Mark. 2004. "Demographic and Socioeconomic Change in Appalachia: Housing and Commuting Patterns in Appalachia." Population Reference Bureau. McCall, Leslie. 2000. "Gender and the New Inequality: Explaining the College/Non College Wage Gap." American Sociological Review 65(2): 234-255. McLanahan, Sara S., Annemette Sørenson, and Dorothy Watson. 1989. "Sex Differences in Poverty, 1950-1980." Signs 15: 102-22. Misra, Joya, Stephanie Moller and Michelle J. Budig. 2007. "Work-Family Policies and Poverty for Partnered and Single Women in Europe and North America" Gender and Society 21(6): 804-827. National Committee on Pay Equity. 2013. Retrieved April 1, 2013 (http://www.payequity.org/). National Conference of State Legislatures (NCSL). 2013. "Health Insurance: Premiums and Increases." Retrieved April 1, 2013 (http://www.ncsl.org/issues-research/health/ health-insurance-premiums.aspx). NC Division of Employment Security. 2013. "NCWorks Online." Retrieved August 1, 2013. (https://www.ncworks.gov/vosnet/Default.aspx). NC Division of Tourism. 2013. "Travel Economic Impact Model: 2012 County Level Visitor Expenditures." Retrieved January 12, 2014. (http://www.nccommerce.com/tourism / research/economic-impact/teim). Pandey, Shanta and Jeoung-Hee Kim. 2008. "Path to Poverty Alleviation: Marriage or Postsecondary Education?" Journal of Family and Economic Issues 29(1): 166-184. Pandey, Shanta., Min Zhan, and Youngmi Kim. 2006. "Bachelor's Degree for Women with Children; A Promising Pathway to Poverty Reduction." Equal Opportunities International 25(7): 488-505. Pearce, Diana. 2012. "The Self-Sufficiency Standard for Maryland 2012." The Maryland Community Action Partnership." Retrieved April 1, 2013. (http://www.selfsufficiency standard.org/ docs/Maryland2012.pdf). Pearce, Diana. 1978. "The Feminization of Poverty: Women, Work, and Welfare." The Urban Social Change Review 11: 128-136. Peterson, Janice. 1987. "The Feminization of Poverty." Journal of Economic Issues 21(1):329-337. Pressman, Steven. 2003. "Feminist Explanations for The Feminization Of Poverty." Journal of Economic Issues 37(2): 353-361. Quinterno ,John., Meg Gray, and Jack Schofield. 2008. "Making Ends Meet on Low Wages: The 2008 North Carolina Living Income Standard." NC Justice Center. Reskin, Barbara F. and Irene Padavic. 2002. Women and Men at Work. 2nd edition. Thousand Oaks, CA: Pine ForgePress. Roxburgh, Susan. 2009. "Untangling Inequalities: Gender, Race, and Socioeconomic Differences in Depression" Sociological Forum 24(2): 357-381. Samuel, Laura J., Szanton, Sarah L., Weiss, Carlos O., Thorpe Jr., Roland J, Semba, Richard D., and Linda P. Fried. 2012. "Financial Strain Is Associated with Malnutrition Risk in Community-Dwelling Older Women." Epidemiology Research International 1-8. Sirota, Alexandra and Edwin McLenaghan. 2010. "Making Ends Meet After the Great Recession: The 2010 Living Income Standard for North Carolina." North Carolina Justice Center. Retrieved November 12, 2013 (http://www.ncjustice.org/sites/default / files/LIVING%20 INCOME %20Standard%20-%202011--REVISED_0.pdf). Simmons, Leigh Ann, Bonnie Braun, and Elizabeth M. Dolan. 2007. "Rhetoric and Reality of Economic Self-Sufficiency Among Rural, Low-Income Mothers: A Longitudinal Study." Journal of Family and Economic Issues (28): 489-505. Thibos, Megan Danielle Lavin-Loucks and Marcus Martin. 2007. "The Feminization of Poverty". The J. McDonald Williams Institute. U.S. Census Bureau. 2010. "FactFinder" Retrieved April 1, 2013 (http://factfinder2.census.gov). Warren, Elizabeth and Amelia Tyagi. 2003. The Two-Income Trap: Why Middle-Class Mothers and Fathers Are Going Broke. New York: Basic Books. Williams, Christine L. Doing "Women's Work": Men in Nontraditional Occupations. New York: Sage Publication, Inc. © 2017
Sociation Today
Return
to Home Page to Read More
Articles Sociation Today is
optimized for the Firefox
Browser
Editorial Board: Editor: George H. Conklin, North Carolina Central University Emeritus Robert Wortham, Associate Editor, North Carolina Central UniversityLawrence M. EppardBoard: Rebecca Adams, UNC-Greensboro Bob Davis, North Carolina Agricultural and Technical State University Catherine Harris, Wake Forest University Ella Keller, Fayetteville State University Ken Land, Duke University Steve McNamee, UNC-Wilmington Miles Simpson, North Carolina Central University William Smith, N.C. State University |