Welfare Dependency and Poverty

Neoliberal rhetoric or evidence-informed choice?

Authored by: Philip Young P. Hong , Brenda Crawley

The Routledge Handbook of Poverty in the United States

Print publication date:  December  2014
Online publication date:  December  2014

Print ISBN: 9780415673440
eBook ISBN: 9781315755519
Adobe ISBN: 9781317627401

10.4324/9781315755519.ch12

 

Abstract

The United States has seen its sovereignty on welfare rights challenged by the neoliberal rhetoric of ending welfare as we know it. The prevailing political argument was that social policies create work disincentives and this in turn traps many people in the state of dependency that exacerbates poverty. At the individual level, the argument was such that long-term welfare recipients have psychological barriers that put them in weak positions vis-à-vis the labor market. Unable to secure stable employment, they end up settling for welfare checks and government subsidies and continue to abuse the system by staying in the state of welfare dependency.

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Welfare Dependency and Poverty

Introduction

The United States has seen its sovereignty on welfare rights challenged by the neoliberal rhetoric of ending welfare as we know it. The prevailing political argument was that social policies create work disincentives and this in turn traps many people in the state of dependency that exacerbates poverty. At the individual level, the argument was such that long-term welfare recipients have psychological barriers that put them in weak positions vis-à-vis the labor market. Unable to secure stable employment, they end up settling for welfare checks and government subsidies and continue to abuse the system by staying in the state of welfare dependency.

Reflecting this problem definition, ending welfare dependency has surfaced as one of the four explicitly stated goals in the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA; P.L. 104–193). This welfare reform legislation created the Temporary Assistance to Needy Families (TANF) that replaced the 60-year-old federal assistance program, Aid to Families with Dependent Children (AFDC). The reluctant welfare state has made a strong statement about removing the role of government in providing the safety net for its citizenry. Evidence from comparative welfare suggests that the United States is one of the least generous welfare states with the highest poverty rate (Smeeding, 2005; Brady, 2009a, 2009b). With weak left party politics in a highly globalized economy, the United States fits the conditions that contribute to its inability to protect its most vulnerable members.

The focus on labor force attachment (LFA) and human capital development (HCD) as market-based solutions for people to escape poverty has continued to maintain dominant status in the push to end welfare dependency and promote economic self-sufficiency (Gueron and Hamilton, 2002; Hong and Pandey, 2008; Kim, 2010). Under the assumption that the psychological barriers that breed welfare dependency would be remedied by working, able-bodied welfare recipients have been recategorized as the dependent “undeserving” poor. These policy choices based on the change of heart have been too quick to penalize the target population by intensifying mandatory work participation. In this regard, the purpose of this chapter is to revisit the U.S. data from a period soon after the implementation of welfare reform during the welfare state retrenchment era and validate the extent to which welfare dependency explains various aspects of poverty—welfare status, employment, poverty, and working poverty.

Background literature

In a brilliant genealogy of the construct known as dependency, Fraser and Gordon (1994) reveal that at various historical times being dependent has been a virtue and has even been required by society in certain types of relationships. For example, women have been expected to be dependent on men as “breadwinners” for the home. As Fraser and Gordon (1994) note:

… people were supposed to be organized into heterosexual, male-headed nuclear families, which lived principally from the man’s labor market earnings. The male head of the household would be paid a family wage, sufficient to support children and a wife and mother, who performed domestic labor without pay.

(p. 591)

It is not only women who have been expected to assume a dependent role in society, but other groups, such as indentured servants, sharecroppers, and the disabled, were forced into dependent status by the structure of society’s labor market arrangements and economic system (Luhman, 2002; Robinson, 2000). Hence, groups were proscribed dependency status without necessarily being ascribed negative social sanction for such a status. Increasingly, however, women who are poor and those with children who use public assistance programs have been and are negatively labeled for their “dependency” status.

In more recent times, individuals and groups from communities that experience chronic conditions of unemployment, underemployment, severely restricted labor market opportunities, persistently underperforming schools, and non-existent or extremely low levels of affordable housing have been labeled as part of the welfare dependent class (Mincy et al., 1990; Niskanen, 1996). In (re)constructing the genealogy, Fraser and Gordon (1994) question the underlying and tacit assumptions regarding current constructions of welfare dependency.

If we can step back from this discourse, however, we can interrogate some of its underlying presuppositions. Why are debates about poverty and inequality in the U.S. now being framed in terms of welfare dependency? How did the receipt of public assistance become associated with dependency…?

(p. 310)

They offer the useful perspective that (U.S.) society’s modern emphasis on the individual personality paves the way for the “moral/psychological register” to reflect itself in viewing both independence and dependence in previously unconsidered ways. This perspective opens the door to viewing the individual as solely responsible for the things that accrue in one’s life. As such, structural forces such as economic recessions and depressions, plant closings, job outsourcing, discrimination, and the like have no place in determining responsibility for (welfare) dependency and poverty (Hong, 2013a). Subsequently, issues surrounding the “isms” such as sexism, racism, ageism, and able-ism remain in the person’s purview for resolution.

Previous research suggests that former welfare experience has an impact each on the likelihood of being on welfare (Cancian et al., 1998; Ellwood, 1986; Zedlewski, 1999) and on employment and earnings (Cancian and Meyer, 2000; Hershey and Pavetti, 1997; Pindus et al., 2000). Caputo (1997) reports that the number of years respondents made use of public assistance programs was the best predictor of becoming self-sufficient. Gottschalk et al. (1994) found that the majority of poor people remain poor for only short periods of time and welfare recipients benefit from welfare for only a few years. Some do, however, go through long-term poverty and welfare dependency.

Human capital has traditionally been found to be a strong predictor of individuals’ economic well-being—educational attainment (Bane and Ellwood, 1994; Cancian et al., 1998; Danziger et al., 1998; Duncan and Hoffman, 1988; Holzer, 1996; Hong and Wernet, 2007; Zahn and Pandey, 2004a, 2004b), job training (Brodsky and Ovwigho, 2002; Hong and Pandey, 2007), and physical health (Beverly and Sherraden, 1997; Hong and Pandey, 2007). Other demographic variables that are found to be associated with poverty are: age, race, gender, marital status, the number of children, and additional household earners (Hong and Pandey, 2007, 2008; Hong and Wernet, 2007).

Based on the review of the literature, this chapter combines the three theoretical perspectives—human capital (Model 1), welfare dependency (Model 2), and demographic characteristics (Model 3)—to explain what welfare reform is designed to accomplish, having former welfare recipients successfully leave welfare, find jobs, and subsequently get out of poverty. The research question being investigated is: Given one’s human capital and demographic characteristics, how does welfare dependency contribute to welfare status, employment, poverty, and working poverty?

Methods

Sample

This chapter uses data from the Core and Topical Module files of the 1996 panel of the Survey of Income and Program Participation (SIPP). Wave 8 (August–November 1998) of the 1996 panel is used because it includes the welfare reform module questions. Data regarding work, job training, health conditions, and welfare history were extracted from Topical Modules 1, 2, and 5. The sample consisted of those who had once received AFDC prior to the 1996 welfare reform. A total of 5,497 observations were found in the sample, which consisted of individuals surveyed in 1998 who were on AFDC at some point before the 1996 welfare reform.

Variables

Welfare status, employment, poverty, and working poverty are dichotomous dependent variables that capture economic well-being outcomes with the value of 1 indicating receipt of AFDC, having a paid job, having total household income less than the official poverty line, and working and living in poverty at the time of the survey in August 1998. The remaining individuals were coded as 0.

Total years on welfare is a dichotomous independent variable that captures whether one has been on AFDC for less than 5 years (=1). 1 Number of welfare spells is a continuous independent variable that measures the number of times a respondent has received AFDC. 2 For human capital variables, low education is a dichotomous variable that reflects whether a respondent has completed less than (=1) or more than or equal to high school education (=0). Job training is a dichotomous variable that captures whether a respondent has received any job training (=1) or not received any job training (=0) in the past. Health is a dichotomous independent variable that captures whether a respondent had work-preventing health conditions (=1).

The demographic control variables examined are respondent’s age, race, gender, marital status, number of children under 18 living in the household, and additional earners. The respondent’s age and number of children under 18 living in the household are continuous variables, while the remaining ones are categorical. Race (non-White=1, White=0), gender (female=1, male=0), and marital status (1 for married and 0 for non-married) are included as factors associated with being poor. A second earner needs to provide about $2,000–$3,700 in earnings in order to offset the increase in family needs required by the additional person (Lerman, 2002), based on which additional household earner is coded 1 if other earner(s) with more than $2,000 annual income is present in the household and 0 if not.

Analyses

This section uses multivariate logistic regression analyses of a set of dichotomous dependent variables—welfare status, employment, poverty, and working poverty—on welfare dependency controlling for human capital and other demographic control variables. Estimation of each dependent variable is conducted by performing a series of empirical tests that compares the effects of human capital, welfare dependency, and demographic control variables. First, the impact of individual models—human capital (Model 1), welfare dependency (Model 2), and demographic control variables (Model 3)—are assessed separately (see Table 12.3). Second, holding Model 1 and Model 3 constant, Model 2 is added to form the combined Full Model (Model 1 + 2 + 3) and to observe whether this yields a statistically significant increase in the log likelihood (see Table 12.4).

Findings

Univariate analyses

As shown in Table 12.1, about 3 percent of the sample (n=145) were recipients of AFDC in August 1998. Approximately 78 percent (n=4,263) reported to be working in a paid job in August 1998. An estimated 11 percent (n=614) had total household incomes at or below the poverty level. The proportion of working poor in the sub-sample of working individuals was 7.11 percent, and slightly less than 93 percent (n=3,960) were working non-poor.

Table 12.1   Descriptive statistics of dependent variables

Dependent variables

N

%

Past-welfare use sample

Welfare status a

5,497

(0) No welfare

5,352

97.36

(1) Welfare

145

2.64

Employment status

5,497

(0) Not working

1,234

22.45

(1) Working

4,263

77.55

Poverty

5,497

(0) Non-poor

4,883

88.83

(1) Poor

614

11.17

Working poverty b

4,263

(0) Work, non-poor

3,960

92.89

(1) Work, poor

303

7.11

Valid N

5,497

Notes:

a  As a percentage of people who were on AFDC at some point in the past before the 1996 welfare reform.

b  As a percentage of people who were on AFDC at some point in the past before the 1996 welfare reform and were working without receiving AFDC in August 1998.

Table 12.2 shows variability in respondents’ characteristics in the sample. Examining the human capital variables, about 14 percent of the respondents had lower than high school education. Having some type of job training was reported at a lower percentage, of about 12 percent. About 20 percent of individuals in the sample reported having health conditions that prevent working.

Table 12.2   Descriptive statistics of independent variables

Independent variables

N

Min

Max

Mean

Std. deviation

Human capital variables

Education < 12 years

5,497

0

1

0.14

0.34

Job training

5,497

0

1

0.12

0.33

Health conditions that prevent working

5,497

0

1

0.20

0.40

Welfare dependency variables

Total years on welfare < 5 years a

1,123

0

1

0.85

0.36

Number of welfare spells (revised) b

1,113

0

17

1.49

1.20

Demographic characteristics

Age (years)

5,497

18

65

34.93

11.71

Race (1=non-White)

5,497

0

1

0.19

0.40

Gender (1=female)

5,497

0

1

0.58

0.49

Marital status (1=married)

5,497

0

1

0.44

0.50

Number of children

5,497

0

8

0.66

1.07

Additional household earner

5,497

0

1

0.82

0.39

Valid N

5,497

Notes:

a  As a percentage of people interviewed in both Wave 1 and Wave 8, who were on AFDC at some point in the past before the 1996 welfare reform and who had reported the number of years on AFDC.

b  As a percentage of people interviewed in both Wave 1 and Wave 8, who were on AFDC at some point in the past before the 1996 welfare reform after dropping 10 extreme cases.

As for the welfare dependency variables, out of those interviewed in both Wave 1 and Wave 8 (n=1,123), about 85 percent had less than five total years on welfare. On average, past welfare recipients had experienced more than one welfare spell.

The demographic characteristics of past welfare recipients indicated that the average age was about 35 and about 80 percent were White. The sample was 58 percent female and 44 percent married. The average number of children was about 0.7, and slightly higher than 80 percent had other earner(s) in the household with more than $2,000 in annual income.

Multivariate logistic regression (LR) analysis

Welfare status. Logistic regression models explaining welfare status were examined (see Table 12.3). Two individual models were found to have good fits between the model and the data—Model 1 (χ2(3)=49.17, p<.001) and Model 3 (χ2(6)=151.97, p<.001). Model 2 was not found to have a good fit. The model fit in the combined perspective was significant—Model 1 + 2 + control (χ2(11)=39.21, p<.001; see Table 12.4). The LR test results in the combined model suggested that adding Model 2 to Model 1 + control did not significantly increase the log likelihood value (χ2(2)=.05).

Table 12.3   Individual logistic regression models explaining various aspects of poverty

Independent variables

Welfare status a

Employment b

Poverty c

Working poverty d

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

Human capital (Model 1)

Education < 12 years

.80 (.20)

***

2.23

−.77 (.09)

***

.46

.94 (.10)

***

2.56

.93 (.15)

***

2.52

Job training

.77 (.21)

***

2.17

.50 (.12)

***

1.65

.49 (.12)

***

1.63

.75 (.15)

***

2.11

Work-preventing health conditions

.79 (.18)

***

2.21

−1.32 (.07)

***

.27

.67 (.10)

***

1.96

.65 (.14)

***

1.92

Constant

−4.12 (.12)

***

1.65 (.04)

***

−2.49 (.06)

***

−2.96 (.08)

***

N=5.497

N=5,497

N=5,497

N=4.263

LL=1291.18

LL=5395.96

LL=3694.24

LL=2110.99

χ2(3)=49.17***

χ2(3)=458.65***

χ2(3)= 154.20***

χ2(3)=75.21***

Welfare dependency (Model 2)

Total years on welfare < 5 years

−.20 (.33)

−.20 (.19)

−.17 (.20)

−.15 (.25)

Number of welfare spells

.06 (.09)

.04 (.06)

.13 (.05) **

1.14

.12 (.06)

Constant

−2.65 (.34)

***

−.90 (.20)

***

−1.28 (.20)

***

−1.65 (.26)

***

N=l,113

N=1,113

N=1.113

N=840

LL=5l 1.15

LL=511.15

LL=1186.16

LL=759.63

χ2(2)=.77

χ2(2)=1.43

χ2(2)=7.00*

χ2(2)=3.71

Demographic characteristics (Model 3)

Age (years)

−.02 (.008)

*

.98

−.02 (.003)

***

.98

−.03 (.004)

***

.97

−.04 (.01)

***

.96

Non-White

.74 (.18)

***

2.10

−.31 (.08)

***

.74

.32 (.11)

**

1.38

.29 (.15)

*

1.34

Female

1.60 (.27)

***

4.96

−.71 (.07)

***

.49

.33 (.10)

***

1.40

.37 (.14)

**

1.44

Married

−.75 (.21)

***

.47

−.03 (.07)

−.17 (.10)

−.25 (.15)

Number of children

.26 (.07)

***

1.30

.002 (.03)

.38 (.04)

***

1.46

.46 (.05)

***

1.58

Additional household

−.69 (.19)

***

.50

.28 (.08)

***

1.32

−1.91 (.10)

***

.15

−1.83 (.14)

***

.16

earner

Constant

−3.94 (.42)

***

2.26 (.15)

***

−.20 (.20)

−.45 (.29)

N=5.497

N=5,497

N=5,497

N=4.263

LL=1188.39

LL=5638.23

LL=623.16

LL= 1809.83

χ2(6)=151.97***

χ2(6)=213.38***

χ2(6)=751.14***

χ2(6)=376.37***

Note:

Notes:

  * indicates p<.05, ** indicates p<.01, and *** indicates p<.001.

a  Dependent variable (Welfare status) = (0) no welfare, (1) welfare.

b  Dependent variable (Employment) = (0) no welfare, (1) welfare.

c  Dependent variable (Poverty) = (0) no welfare, (1) welfare.

d  Dependent variable (Working poverty) = (0) no welfare, (1) welfare.

Table 12.4   Full logistic regression models explaining various aspects of poverty

Independent variables

Welfare status a

Employment b

Poverty c

Working poverty d

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

(se())

Sig.

Odds ratio

Human capital (Model 1)

Education < 12 years

.56 (.31)

−.86 (.18)

***

.42

.81 (.20)

***

2.25

.63 (.27)

*

1.87

Job training

.09 (.27)

.58 (.16)

***

1.79

−.43 (.17)

**

.65

−.29 (.21)

Work-preventing health conditions

.62 (.27)

*

1.86

−1.16 (.16)

***

.31

.69 (.18)

***

2.00

.49 (.24)

*

1.64

Welfare dependency (Model 2)

Total years on welfare < 5 years

−.08 (.35)

.18 (.21)

−.15 (.23)

−.23 (.29)

Number of welfare spells

−.0003 (.10)

.05 (.07)

.04 (.06)

.04 (.07)

Demographic characteristics (Model 3)

Age (years)

−.02 (.02)

−.01 (.01)

−.04 (.01)

***

.96

−.06 (.02)

***

.94

Non-White

.47 (.27)

.08 (.18)

.38 (.18)

*

1.46

.32 (.22)

Female

−1.30 (.68)

.58 (.61)

−.40 (.61)

.77 (1.08)

Married

−.11 (.32)

−.73 (.18)

***

.48

−.11 (.20)

−.16 (.26)

Number of children

.07 (.11)

−.03 (.06)

.32 (.07)

***

1.38

.33 (.09)

***

1.39

Additional household earner

−1.04 (.30)

***

.35

.05 (.18)

−1.83 (.19)

***

.16

−1.85 (.25)

***

.16

Constant

−.66 (1.10)

1.47 (.80)

1.01 (.83)

.04 (1.29)

N=1,113

LL=472.72

χ2(11)=39.21***

N=1,113

LL=1106.83

χ2(11)=133.26***

N=1,113

LL=954.32

χ2(11)=238.84***

N=840

LL=616.75

χ2(11) = 146.44***

AIC=.45

LR test: χ2(2)=.05

AIC=1.02

LR test: χ2(2)=1.35

AIC=.88

LR test: χ2(2) = 1.05

AIC=.76

LR test: χ2(2)=.86

Note:

Notes:

  * indicates p<.05, ** indicates p<.01, and *** indicates p<.001.

a  Dependent variable (Welfare status) = (0) no welfare, (1) welfare.

b  Dependent variable (Employment) = (0) not working, (1) working.

c  Dependent variable (Poverty) = (0) poor, (1) non-poor.

d  Dependent variable (Working poverty) = (0) working and non-poor, (1) working poor.

Employment status. A series of logistic regression analyses of employment status on three sets of independent variables were examined (see Table 12.3). Two individual models—Model 1 (χ2(3)=458.65, p<.001) and Model 3 (χ2(6)=213.38, p<.001)—were found to have good fits between the model and the data. Model 2 once again did not yield significant results. The combined perspective displayed a significant model fit—Model 1 + 2 + control (χ2(11)=133.26, p<.001; see Table 12.4). The LR test result for adding Model 2 to Model 1 + control was not significant (χ2(2)=1.35).

Poverty. Logistic regression models explaining poverty were examined in sequence (see Table 12.3). All three individual models had good fits between the model and the data—Model 1 (χ2(3)=154.20, p<.001), Model 2 (χ2(2)=7.00, p<.05), and Model 3 (χ2(6)=751.14, p<.001). The combined model was also found to have a significant model fit—Model 1 + 2 + control (χ2(11)=238.84, p<.001). The LR test result did not yield a significant increase in the log likelihood value after adding Model 2 to Model 1 + control (χ2(2)=1.05).

Working poverty. The final column of Table 12.3 presents a series of individual logistic regression models explaining working poverty. Model 1 (χ2(3)=75.21, p<.001) and Model 3 (χ2(6)=376.37, p<.001) were significant, while Model 2 was not significant. The model fit in the combined perspective was significant—Model 1 + 2 + control (χ2(11)=146.44, p<.001). The LR test results revealed that adding Model 2 to Model 1 + control did not significantly increase the log likelihood value (χ2(2)=.86).

Discussion and conclusion

This chapter provided empirical evidence of past welfare recipients in 1998 from the SIPP data that both the human capital perspective (Model 1) and demographic characteristics (Model 3) explain significantly the likelihood of all four dependent variables throughout the analyses in individual and combined models. Welfare dependency, however, was found to be significant only in the individual model explaining poverty but not with those explaining welfare status, employment, and working poverty. The number of welfare spells was one welfare dependency variable that significantly affected the likelihood of living in poverty. Further, no significant effects were found of any of the welfare dependency variables in the combined model. Therefore, there is weak evidence as to whether welfare dependency—the length of welfare experience and the number of welfare spells—contributes to the various dimensions of poverty.

It is interesting to find that the null findings on welfare dependency further confirmed what the framers of the welfare reform had envisioned—to exchange welfare payment with salaries. Siding with the political rhetoric rather than relying on comprehensive evidence-informed policy making, America seem to have embarked on a vast experiment, much of it based on the premise that penalties or sticks will move people from dependency to independence or selfsufficiency, and eventually from poverty to economic security and financial stability (Hong, 2013b). In fact, this problem definition has been effectively mobilized in the political arena to reaffirm the government’s position to turn its back on people living in poverty.

Every conceivable human characteristic, trait, and status has been implicated in the label and condition of welfare dependency. Additionally, numerous societal institutions, such as family, education, the economy, and government, have been plugged into the huge net of explanations, rationales, causes, and reasons for the “condition” of welfare dependency. Certainly no single factor can be tagged as fully responsible for this condition. However, the political rhetoric has subscribed to micro-level, psychological, attitudinal, behavioral, and cultural explanations, often overlapping with each other (Bartholomae et al., 2004; Fraser and Gordon, 1994; Niskanen, 1996). Micro-level explanations have been met with a victim-blaming approach to social engineering of individuals as policy choices—whether moral, ethical, character-altering, and/or behavioral in nature—intended to remedy welfare dependency (Niskanen, 1996).

Some contending views posit at the mezzo level that welfare dependency can best be understood by examining family structure and dynamics (Antel, 1992; McLanahan, 1988; Taylor and Barusch, 2004). Others at this level turn attention to the nature and structure of communities and how these impact the life chances for individuals (Wilson, 1996). At the macro level, the structural vulnerability thesis implicates human capital as a manifestation of low-wage workers’ weak positions in societal institutions such as but not limited to the economy, labor market, education, and wages/salaries (Crew and Eyerman, 2001; Hong and Pandey, 2007; Rank, 2004). However, these views were incapable of withstanding the dominant individually based problem definition of welfare dependency.

It is apparent that welfare dependency was tagged with a negative image and fell prey to the political rhetoric as a tool to support welfare reform. Subsequently, it was transformed into self-sufficiency by putting a positive spin on the “old” welfare dependency that was deemed to be plaguing the welfare system. The triumphant neoliberal rhetoric has set the tone for poverty politics in the United States. Therefore, this chapter contributes to the redefinition of how poverty is viewed in the U.S. policy-making process. According to DiNitto and Cummins (2007), “poverty has gone from being a problem of too little income to a problem of dependency” (p. 118). Then, the problem of dependency became the goal of self-sufficiency in a new policy reality post-welfare reform.

This reality is too real to do away with as the United States continues to downsize its welfare state within the context of its government being structurally dependent on global capitalism and market performance (Hong, 2008). This chapter proposes to transform the global welfare state crisis into an opportunity for organizing bottom-up strategies for invigorating workforce development and nudging the local labor market to become an inclusive system. While one can critique the concept of self-sufficiency for its lack of clarity, therefore making it difficult to measure and evaluate its success outcome, it opens the opportunities for social investment for empowering low-income jobseekers—not only in their “personal responsibility” but also their “work opportunities” to sustain their individual efforts (Cooney, 2006; Hong, 2013b; Hong et al., 2009; Sandlin, 2004).

If the negative image of welfare dependency has been effectively used by the political rhetoric to individualize the issue of poverty and dismantle the welfare system as we know it, self-sufficiency could present a positive opportunity. Reclaiming power and ownership of the concept of self-sufficiency by reframing it as personal empowerment could open the doors to transforming the often-blamed “debilitating” individual deficiencies into positive motivations, work-readiness, and economic success among low-income jobseekers (Hong et al., 2009). This transformation demands structural matching of the local labor market system and other social institutions to nurture human development and sustainability (Hong, 2013b).

While the approaches offered by the policy reality may have stayed individualistic in nature, the anticipated community-based, bottom-up change could bring about macro social change if the resources are capitalized on comprehensively to maximize the potential social investment from both the private and public sectors. Without doubt, empowerment-based workforce development programs need to be encouraged and transitional employment planning would need to break away from labor market dependency—relying on the demand side of the labor market—and tailor labor market development to the needs and efforts of low-income jobseekers.

Notes

This variable is equivalent to Indicator 7 (Dependence Spell Duration) examined by the U.S. Department of Health and Human Services (2001), which was designed to tap into the dynamics of welfare receipt and welfare dependence. The issue of spell duration is particularly important in light of the time limits that have been enacted under state TANF programs.

This measurement is consistent with Indicator 10 (Long-Term Receipt) of those identified by the U.S. Department of Health and Human Services (2001). Indicator 10 focuses on individuals who leave welfare programs and cycle back on after an absence of several months. It was calculated to examine the cumulative amount of time individuals receive assistance over a period of several years.

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