* License-exempt childcare is care provided by a relative or non-relative, for no more than the number of children in the family of the provider and one other family, and where no other provider qualifications or facility standards are required by the state of California
The State of California spent nearly 100million dollars in 1998 for subsidized childcare payments to over 300 thousand families enrolled in the state welfare program, CalWORKs. Approximately seventy percent of these funds went for payments to the "license-exempt" sector (Public Welfare in California - Annual Report, 1997-98). The situation in Fresno County is similar, with one-third of enrolled children of CalWORKs recipients using license-exempt care. The proportion is higher for infants, with 38 percent of them using exempt care (Supportive Services, Inc., 1998, personal communication). As Fresno County employs a "12-week rule" for the maximum age of the child prior to mandatory enrollment of CalWORKs recipient mothers in work or work-related activities, the stability of child care arrangements (especially for infants) becomes vital to the development of sustainable employability.
Given its agriculture-based economy, Fresno County does not compare well with the other (57) counties in the state on most key measures of child wellbeing. The county ranks 52 in low-income children, 56 on children receiving CalWORKs, and 44 on foster care rate. These rankings parallel to those in the social and economic areas. The county ranks 46 in unemployment, 54 on mothers with less than 12 years of education, 53 in high school dropout rate, and 42 on infant mortality and teen births (Children Now, 1999). Given the relatively disadvantaged social and economic environments, the availability of suitable childcare for low-income families, especially CalWORKs families, is therefore important. The needs for better understanding the choice and the stability of childcare arrangements among the families, especially CalWORKs families, are clear.
Prior research in this area has indicated that stability of childcare arrangements is directly linked to child wellbeing, and that the choice of providers significantly affects the stability of the arrangements (Hofferth, 1997). A number of factors have been shown to significantly affect the choice of license-exempt providers for very young children. These factors include age of child, service hours of providers, lack of alternatives, and cost of care (National Center for Children in Poverty, 1998). Nevertheless, with the exception of Queralt and Whitte (1998), research in this area rarely examines the effects of spatial and location-specific factors, such as the care provision capacity of neighborhoods, on the choice and stability of childcare arrangements. As such the use of Geographic Information Systems (GIS) technologies have the potential to complement traditional analyses, enabling new insights into the patterns and processes of childcare arrangements.
Fresno County is one of the few counties in California to undertake systematic, GIS-based, analysis of the stability of childcare arrangements. The analysis is made possible because the county has developed a countywide GIS system, which contains more than 100 layers (or themes) including a point address file with 340,000 records. This layer, along with several others, is central for deriving the patterns of childcare providers and their families, thereby enabling inferences to be drawn regarding the spatial choice of childcare arrangements.
This research is a two-year study funded by the California Social Work Education Center (CALSWEC), whose purpose is to promote the advancement of child welfare practice through the support of research and graduate social work education. The primary objectives of this research, based on a combination of GIS technologies and traditional statistical analysis, are twofold. The first is to examine major patterns of childcare delivery, including those of utilization and stability of different types of childcare arrangements. The second objective is to determine the factors influencing parental choice of providers and the stability of childcare arrangements. In addition, this research aims at demonstrating the suitability of GIS technologies for managing childcare service delivery by other counties in California, and the utility of applying the technology for social services and child welfare research and education.
In its first year the research
team has made extensive use of ArcView, a leading GIS program, to perform
spatial analysis to support the infrastructure for childcare and planning
of services to children and families in Fresno County. The first stage
of research has explored some of the effects of welfare reform upon low-income
families whose children are enrolled in childcare. Along with the findings
from the second stage, the results of this research will be used to enhance
the technology-specific content of graduate social work education in the
State of California. The project will also yield the first, fully constituted
childcare provider shapefiles for inclusion with the GIS infrastructure
in Fresno County, California.
Research Questions
With respect to the two objectives, this study has five major research questions:
1. What are the patterns of childcare utilization over the study period?
2. What is the level of stability (duration of care) of childcare arrangements?
3. What demographic characteristics (e.g. race, gender, age, household status, ethnicity, income) and locational factors (e.g. provider capacity of individual neighborhoods, distance from parental employment and childcare) are associated with particular patterns of childcare utilization and stability?
4. What reasons do parents give to explain their choice of and change or termination from childcare arrangement?
5. What measures of childhood wellbeing might be developed for
future evaluative study of Fresno County's childcare system?
Collaboration
This research is not possible without extensive collaboration and participation of key childcare service agencies in Fresno County. Close collaboration with relevant organizations is especially critical for research on closed systems such as childcare with established roles, functions, and political alliances. Fortunately, because of extensive pre-existing working relationships, the research team was and continues to be able to secure collaboration from four participating agencies in the county. The data repositories that the four agencies maintain represent approximately 90 percent of the childcare population in the county. The repositories, which include data on childcare providers, families of enrolled children, and enrolled children, are critical for the research. However, the degrees of collaboration vary between the participating agencies. While the research team was able to secure most data from the participating agencies, certain data including families and children receiving care under the federal Head Start program and county government childcare services agency were not accessible in the first year of the project. Part of the problem stems from system incompatibility and differing reporting standards of the agencies. Ongoing efforts are being made to overcome these obstacles in the second year of the project.
To maintain ongoing interests
and collaboration, the research team holds regular meetings with representatives
of all the participating agencies. In addition, the team gave a total of
five internal progress reports to the agencies since October 1999, with
the contents of the reports emphasizing the analysis of the data provided
by the respective agencies.
Confidentiality
A Memorandum of Understanding
with the County Human Services System covering exchange of confidential
case data for CalWORKs participants and related case-level data was an
essential accomplishment of the early project activity. The project director
and county agency further narrowed the scope of the agreement to include
only one of eight colleges within the university, thus limiting the probability
of inappropriate release of confidential data. A joint committee was established
to review current and future research interests, and a protocol for identifying
priority research areas was developed. A liaison was appointed from both
the county agency and the college, and periodic meetings were scheduled
to continue dialogue. The county/university agreement was a complicated
endeavor; it took three months to promulgate. This may be considered a
modest timeframe, particularly in light of the fact that three sets of
attorneys were involved in the review; and final approval was required
by the county Board of Supervisors, the University Provost, and the College
Dean. Additional agreements were concluded, with much less difficulty,
with two non-profit organizations permitting ongoing data exchange with
the research team and the graduate students the team members supervise.
Data and Methodology
With the confidentiality agreements, the research team attained needed data, which cover providers, families of enrolled children, and enrolled children, for the study from the participating agencies. All three sets (providers, families, and children) of data contain address information, which facilitate point address mapping through geo-coding in ArcView. The key variables in the provider files central to the study include type of care, hours of operation, and number of slots; whereas those in the families and children include size of family, ages of enrolled children, and employment status of the parents. The families file of one participating agency further contains the address of the employers of the parents, an important piece of information for examining the association between the work location of parents, especially that of mothers, and the location of the providers of the respective families.
Since the coverage and reporting standards vary between agencies, extensive efforts were devoted to standardizing and merging the data files. These efforts include developing task-specific programs to remove redundant records for identical cases, using macro languages to re-define database structures, and verifying merged results through both manual and computerized routines. A master file, in .dbf format, relating the providers to their client families and children was created for each of the participating agencies. A grand master file relating all the information from all the participating agencies was also created.
The master file of each of the agencies and the grand master file were geo-coded against the point address file maintained by the County of Fresno. Two themes, one pertaining to the pattern of providers and the other families, were created for each of the files. With the two themes and the specific spatial query function in ArcView, the locational association between a provider and its client families is displayed in a view. This display enables actual traveling distance to be measured between a provider and any one of its client families, which constitutes the dependent variable in the preliminary stages of constructing a socio-econometric model.
Given the complexity of analysis across agency boundaries and the relatively large size of individual master files, the first stage of socio-econometric modeling effort involved a 10 percent sample of one of the agency master files. The master file of this agency has a total of 2,632 records (enrolled children), with the sample created based on a systematic random method containing 242 useful cases for analysis. Given the relatively small number of cases, the findings in the following section should be considered indicative. Nevertheless, preliminary analysis with a portion of the data from the county data repository, which contains most of the childcare population in the county, shows similar empirical tendencies.
It is important to note that
the data structure for examining the stability of childcare arrangements
are different from that for investigating the locational characteristics
of providers and their client families. To detect the stability of the
arrangements repetitive transactional information, usually on a monthly
basis, between a client family and its provider(s) is required. This type
of information is available from one participating agency and from the
County Human Services System. Given the peculiar data structure, customized
programs were developed to enable analysis of this nature. As with the
socio-econometric modeling effort described above, to minimize problems
associated with the use of multiple databases, the study at this stage
confines the analysis to the transactional information of the participating
agency for the period July 1998 to June 1999. Therefore the findings on
the stability of childcare arrangements are partial. The transactional
database of the participating agency analyzed contains a total of 2,492
records. These records are related to 370 children.
Findings
Locational Distribution of Providers and Families
Using the county database Figure 1 shows that, within the city limit, childcare providers concentrate in the central-southern portion (hereafter central-south where appropriate, defined as the areas south of Shaw Avenue) of the city. Of the three types of providers, more than 90 percent of exempt care providers are in central-south. The corresponding percentages for the two types of licensed care providers-childcare center and family daycare home-are 87 and 68 percent, respectively.
[Figure 1: Locational Distribution of Childcare Providers in the
City of Fresno]
The locational distribution
of families with children enrolled generally follows that of the providers.
Of all the families within the city limit, approximately 95 percent are
located in the central-southern portion of the city. Figure 2 shows the
locational distribution of the families associated with county childcare
providers.
[Figure 2: Locational Distribution of Families with Children Enrolled in the City of Fresno]
Spatial Distribution of Provider Capacity
Although the locational distribution of providers coincides with that of families, the smaller capacity of exempt providers (usually 2 to 4 children) and the larger size of the families in central-south highlight the inadequacy in the provision of childcare services in this portion of the city. Using the number of slots of the providers, Figure 3 shows the spatial distribution of the capacity of licensed providers in the city of Fresno. A capacity map using all types of providers has not been attempted at this point, as capacity data for exempt care providers will need to be re-entered manually.
[Figure 3: Spatial Distribution of Provider Capacity in the City of Fresno]
Figure 3 shows that the northern part of the city has a significant share of licensed care capacity. This is because a larger proportion of large daycare centers is located in this part of the city. Although the supply imbalance situation in central-south is modulated by the concentration of exempt providers in this area, the overall effect is limited because of the small capacity of this type of provider.
Care Demand
With the 1997 estimation for children of 5 years or younger at the census block level, the study derives the spatial structure of childcare demand for the city, as Figure 4 shows.
[Figure 4: Spatial Structure of Childcare Demand in the City of Fresno]
Figure 4 shows the presence of three major areas of concentration of children 5 or younger. These three areas are southeastern, northeastern, and the western part of the city. A comparison of Figures 3 and 4 indicates that the southeastern and western part of the city do not have adequate childcare service capacity.
Care Supply-Demand Analysis
Based on the patterns of supply and demand derived in Figures 3 and 4, the study compares the number of slots available for children and the number of children 5 or younger for every neighborhood in the city. At this point the analysis is conducted at a 5-digit zip code level. Detailed tabulation will be made at a census block level in the future. Assuming one of every three children requires some form of care, a demand-supply ratio (number of children 5 or younger divided by number of childcare slots) of 3 or smaller indicates a supply adequate condition. The larger the ratio above 3, the greater is the supply deficit condition. Figure 5 shows the demand-supply ratio of childcare services in the city at a 5-digit zip code level.
[Figure 5: Areas with Inadequate Provision of Childcare Arrangements (Supply Deficit Condition) in the City of Fresno]
The analysis strongly indicates
that the southeastern part and to a less extent the western part of city
have a supply deficit condition. Families in these two parts of the city
are likely to have more difficulties in securing acceptable childcare arrangements;
they may be forced to travel greater distances to receive services.
Travel Distance
Using the 10 percent sample of the master file of one participating agency, Table 1 shows the travel distance by provider type and by zip code area.
Table 1: Travel Distance of Families by Provider Type and by Zip Code Area
Travel Distance
Number of
Category
(miles)
Cases
---------------------------------------------------------------------------------------
Providers
Licensed
3.15
142
Exempt
3.81
100
Zip Code Areas
North (93612, 650, 710, 711, 720)
4.12
30
Central-South (93701, 704, 705,
721, 726, 728)
2.91
94
West (93722)
3.18
22
Southeast (93702, 703, 727)
3.76
55
---------------------------------------------------------------------------------------
The figures in Table 1 shows that families with exempt providers travel greater distance than those with licensed providers. The average distance that all the families (with exempt and with licensed providers combined) travel is 3.42 miles. With respect to different parts of the city, families in the northern part travel greater distance to secure care services, whereas those in other parts of the city have a travel distance near or below the average of all the families.
Stability of Care
Given the restrictions of most subsidized programs, the childcare arrangements in the city and county of Fresno have a relatively stable structure. Of the 370 children associated with one of the participating agencies during the period July 1998 to June 1999, only 18 percent changed their arrangements. Table 2 shows the stability of care arrangements derived from the transactional records of the participating agency.
Table 2: Stability of Childcare Arrangements of a Participating Agency
Number of Providers A Child
Number of Percent of
Had During 7/98 to 6/99
Children
All Cases
----------------------------------------------------------------------------------
One
302
82
Two
59
16
Three
9
2
----------------------------------------------------------------------------------
Toward a Socio-Econometric Model
Preliminary
The findings elaborated in the Findings Section above suggest a variety of factors influence the selection, utilization, and stability of childcare arrangements in the city and county of Fresno. To better understand the care selection and utilization behaviors of families in different neighborhoods, the study attempts to construct a socio-econometric model using the actual travel distance between a provider and its client family as the dependent variable. As regards the independent variables, the study includes two location-specific variables-whether a family is in a supply deficit area (a variable derived from the supply-demand structure of childcare in the above section), and whether provider's location in on-mother's-way-to-work (another variable derived from geo-coding the work location of the mothers. Along with other attribute information already existing in this agency master file, the socio-econometric model contains the following independent variables:
Variable
Value
----------------------------------------------------------------------------------------------------------
Whether provider's location is on-mother's-way-to-work
1 = Yes, 0 = No
Whether a family is in a supply deficit area 1 = Yes, 0 = No
Provider type 1 = Licensed, 0 = Exempt
Provider capacity (small: = < 20 persons; large: > 20 persons) 1 = Large, 0 = Small
Family size (small: 0 - 4 persons; large > 4 persons) 1 = Large, 0 = Small
Family ethnicity
1 = Non-Caucasian,
0 = Caucasian
Family with more than one children age group
1 = Yes, 0 = No
(age group 1 : 5 years or younger, age group 2 :
older than 5 years)
Family with mother working
1 = Yes, 0 = No
----------------------------------------------------------------------------------------------------------
Sample Characteristics
Cross-tabulation analyses on the sample data set show that, within the city limit, approximately 84 percent of the providers and 84 percent of the client families are in the central-southern portion of the city. Although the two proportions are essentially the same, the central-south has a higher percentage of families (33 percent) that are large in size. The area also has a higher proportion of providers (40 percent) that are exempt providers (the corresponding percentages for North Fresno are 17 and 30 percent, respectively). These higher percentages are associated with the concentration of ethnic minority families (primarily Latino, Southeast Asian and African American) in central-south Fresno, which tend to be larger in size, and to the greater propensity of ethnic minority families to choose exempt care providers. The difference between family ethnicity and family size, and that between family ethnicity and provider type, are significant at the 0.05 level. These findings concur with those in the Findings Section, suggesting the sample data set is representative of the respective population.
The Model
The construction of the socio-econometric model to explain the patterns of childcare utilization and stability in the county of Fresno is at its infant stage at the time of this writing. Initial attempts did not produce significant correlation between the dependent and the independent variables. This situation was anticipated at the beginning; the model needs to incorporate more variables that will be derived from the master files and from an ongoing questionnaire survey with the client families of a participating agency. The data from the survey, which addresses a variety of questions concerning care utilization and stability, will be used for fully developing the model in the summer of 2000.
Nevertheless, significant association is found between the independent variable (actual travel distance between a provider and a client family) and three of the dependent variables (whether a family is in a supply deficit area, provider type, and family with mother working). The significant association between actual travel distance and supply deficit condition (Chi-Square = 5.16, P = 0.02) shows that a larger percentage of families in supply deficit areas select providers that are nearby (within 2 miles). This finding goes against the common assumption that, because of the limited number of childcare slot, families in supply deficit areas will have to travel further to receive services. This peculiar situation arises because most of the supply deficit areas are economically disadvantaged neighborhoods. Families in these areas tend to have less information about childcare options; they are either unable or unwilling to travel greater distance for receiving services. This highlights that a large percentage of families in supply deficit areas are trapped; the parent(s) may have no choice but to leave their children home alone or with informal care givers, should they go to work. This is potentially a serious problem, as a significant portion of these disadvantaged families are single-parent households.
The association between actual travel distance and provider type (Chi-Square = 3.07, P = 0.08) indicates that a larger percentage of families using exempt providers travel greater distance (67 percent of families using exempt care travel 2 miles or more, versus 55 percent for families using licensed care). Most of the exempt providers are relatives of the respective client families, reflecting familiarity or personal trust an important determinant for childcare arrangements among this group of families. It is important to note that most of these families are in supply deficit areas. The existence of family ties provides an important avenue for families in these areas to secure acceptable childcare arrangements. This option however, is limited to families with such ties. Families that are new to Fresno would not be able to exercise this option.
The association between actual travel distance and families with employed mothers (Chi-Square = 3.64, P = 0.06) reveals a significant proportion of families with the mother employed travel greater distances (62 percent of families with employed mothers travel 2 miles or more versus 31 percent for families with the mother not working). This situation is partly attributable to the priority some families assign to the proximity of child care provider to the work location. Although only 5 percent of the mothers in the sample data set do not work, the short travel distance suggests that these families have limited options for choosing childcare providers.
There were no significant
association between the dependent variable and the other independent variables.
This lack of association indicates that whether provider's location is
on-mother's-way-to-work, provider capacity, family size, family ethnicity,
and family with more than one children age group are not important provider
selection criteria for most families. However, as the modeling effort is
at its infant stage, it remains to be seen the extent to which these independent
variables influence the dependent variable. In the second year of this
study all the existing variables will be refined, with the addition of
other important variables including the income level and car ownership
of the families from other sources and from the survey.
Summary and Conclusion
With the use of GIS technologies, the study complements traditional analyses of childcare utilization and stability by incorporating spatial and location-specific variables in a model building effort. The inclusion of these variables enables a better understanding of the neighborhood environment a family is in and the effect of that environment on a family's behavior on childcare provider selection and utilization. In the city of Fresno the study found that families in supply deficit areas are trapped; the parent(s) may be forced to leave their children unattended at home when they are at work. The study also found that familiarity or personal trust is an important care arrangement determinant for families with such ties. These families are willing to travel greater distance for trusted services.
The socio-econometric model
for systematically explaining the care selection and utilization behaviors
of families is currently at its infant stage of development. The second
stage of the model building effort will include a refined set of existing
variables and new variables from other sources and an ongoing survey. The
survey will be completed by the end of June this year, generating detailed
data related parental choice, transportation and employment location from
approximately 500 families. The research team expects to fully achieve
the two primary objectives stated in the earlier portion of this paper.
Acknowledgments
Financial support for this study is provided by the California Social
Work Education Center (CALSWEC) located at the School of Social Welfare,
University of California, Berkeley
References
Adams, G. & Schulman, K. (1998). "California: Child care challenges." Children's Defense Fund. Retrieved November 6, 1999 on the World Wide Web: http://www.childrensdefense.org/childcare/newsletters/2001_0904.php
Anderson, F. (1996). Meeting the needs of low-income families through family childcare professional development and consumer education. 1996 Child Care Aware Conference Report. Rochest, MN: Child Care Aware.
Bania, N. & Coulton, C. (1997). "A neighborhood information capacity for community building, policy analysis and evaluation." Center on Urban Poverty and Social Change. Mandel School of Applied Social Sciences. Case Wester Reserve University. Cleveland, OH.
Becerra, R. & Chi, I. (1992). Child care preferences among low-income minority families. International Social Work, 35, 35-47.
California Department of Education. (1997). Guiding principles to implement welfare reform in specific education policy areas. Retrieved October 1998 on the World Wide Web: http://www.cde.ca.gov
Chick, K. (1996). Caregivers of Quality: One Mother's Search for Child Care. Early Childhood Education Journal, 23(1), 149-151.
Children Now (1999). California report card 99: How our youngest children are faring. Retrieved March 10, 2000 on the World Wide Web: http://www.childrennow.org/california/RC99/reportcard-99.html
Chilman, C. S. (1995). Programs and policies for working poor families: Major trends and some research issues. Social Service Review, 69(3), 515-524.
Coulton, C. & Hollister, R.. (1998). Measuring comprehensive community initiative outcomes using data available for small areas. In K. Fulbright-Anderson, A.C. Kubisch, & J.P. Connell (Eds.), New approaches to evaluating community initiatives: Vol. 2. Theory, measurement, and analysis (pp. 165-220). Washington DC: The Aspen Institute Roundtable on Comprehensive Community Initiatives for Children and Families.
Cryer, D. & Burchinal, M. (1997). Parents as Child Care Consumers. Early Childhood Research Quarterly, 12, 35-58.
Department of Social Services, Health and Welfare Agency, State of California (1997-98). Public Welfare in California: Annual Report 1997-1998.
Ellwood, S. and Leitner, H. (1998). GIS and community-based Planning: Exploring the Diversity of Neighborhood Perspectives and Needs Cartography and Geographic Information Systems 25(2): 77.
Family Impact Seminar & The AAMFT Research and Education Foundation. (1990). "Quality in child care: What is it and how can it be encouraged?" Seminar conducted in a series of monthly seminars for policy staff, entitled Social Policy: The Emerging Agenda, 6-29.
Frankel, A. J. (1991). The dynamics of day care. Families in Society: The Journal of Contemporary Human Services, 72(1), 3-10.
Frankel, A. J. (1994). Family day care in the United States. Families in Society: The Journal of Contemporary Human Services, 75(9), 550-560.
Galinsky, E., Hoyes, C. Kontos,S. & Shinn, M. (1994). The study of children in family child care and relative care-key findings and policy recommendations. Young Children, 50(1), 58-61.
Harris, T. (1998). Empowerment, Marginalization and " Community -integrated" GIS. Cartography and Geographic Information Systems 25(2):67
Hoefer-R.A; Hoefer-R; Tobias-R.A (1994). Geographic information systems and human services. Journal of Community-Practice.1(3): 113-28, 1994.
Hofferth, S. (1989). What is the demand for and supply of child care in the United States? Young Children, 44(5), 28-33.
Howes, C. (1986). Quality indicators for infant-toddler child care. Symposium conducted at the annual meeting of the American Educational Research Association. 2-21.
Lally, J. R., Torres, Y., & Phelps, P. (1994). Caring for infants and toddlers in groups: Necessary considerations for emotional, social, and cognitive development. National Center for Clinical Infant Programs, 14(5), 1-35.
Los Angeles Welfare Reform Coalition. (1999). The Los Angeles welfare reform center. Retrieved on the World Wide Web: http://www.welfarewatch.org/county/nloct.
Marshall, N. (1991). The changing lives of young children: Infant child care as a normative experience. Families in Society: The Journal of Contemporary Human Services, 72(8), 496-501.
Meyers, K.K. (1995). Child care, parental choice, and consumer education in JOBS welfare-to-work programs. Social Service Review, 6(4), 679-702.
Novotny, P. & Jacobs, R.H. (1997). Geographic information systems and the new landscape of political technologies. Social sciences computer review. 15 (3), 264-285.
Obermeryer, N. J. (1998). The Evolution of Public Participation GIS Cartography and Geographic Information Systems 25(2):65.
Queralt-M; & Witte-A.D (1998). A map for you? Geographic information systems in the social services. Social Work.43(5), 455-469.
Schlossberg, M. (1998). Asset Mapping and community development planning with GIS: A look at the heart of West Michigan United Way's Innovative Approach . Paper presented at the 27th Annual Meeting of the Association for Research on Nonprofit Organizations and Voluntary Action, Seattle, WA.
Spade, M. (1996). Mapping the needs of the poor. Clearinghouse review., 138-145.
Tompkins, P. L. and Southward, L. H. (1998). Geographic Information Systems (GIOS): Implications for Promoting Social and Economic Justice Computers in Human Services 15(2/3):209-226.