PACE WORW PM 1% R SIRIH 01;; M Child-Care Aid and Quality for California Families: Focusing on San Francisco and Santa Clara Counties August2001 INSTITUTE or mm 1 , J .J ‘7“ 1):» YAYJAAE STUD/[:3 l {445573,‘5i93‘r NTAL (-,~.A. _, -. ,-~. rr-H “,5 3‘ Ma. \‘ x! >5- (”1" UNlVERSll‘Y or CALlF onmm Growing Up in Poverty Project Policy Analysis for California Education University of California, Berkeley and Stanford University Bush Center in Child Development and Social Policy Yale University Teachers College, Columbia University summary The Growing Up in Poverty (0UP) Project aims to learn from the diverse families who are entering new welfare programs and to explore variability across their neighborhoods. Our earlier national report, Remember the Children (2000), detailed how the overall quality of center-based care selected by welfare—poor mothers in California was significantly higher than the quality of care selected by corresponding samples of women in Connecticut and Florida. The quality of home-based care, however was quite uneven within all three states. Since 1996, millions of single mothers with preschool-age children have entered revamped welfare programs, relying on work-first and time-limited aid. During the second half of 1998, we invited over 1,000 women to join the GUP Project. Participating mothers then took part in an initial round of interviews, visits to their child-care settings, and assessments of their children's early develop- ment. During this wave 1 data collection period, the average child was 22 months old. Gauging the quality of centers and home-based child care. This paper focuses on the study's 410 participating mothers and their families who live in Santa Clara and San Francisco counties. It describes the quality of their child-care arrangements and their propensity to use subsidies for which most were eligible. This new analysis moves beyond summary indices to identify how quality can be improved in both counties. Overall, we observed comparatively moderate to high quality in center-based programs and preschools. The array of child activities and educational content of home-based settings was not impressive. We spotlight areas where the quality of centers and home settings remain weak, aiming to inform state and local policymakers on how to best target new funding. Our observations revealed that more work remains in providing ample language and reading materials, and time for providers to read and exercise communication skills with young children. One dilemma within the field of child care is the tendency for many mothers to view kith and kin arrangements—despite their uneven educational quality—as preferable to centers and preschools. Mothers reported that kith and kin providers are more respectful of their own parenting practices, and more flexible in terms of when the caregiver is available. Mothers also said they believe their child receives more individual attention, compared to those using centers. Which low-income mothers draw child-care support? Women who select centers or preschools often receive a subsidy to cover the cost. But only a small fraction of women selecting home-based arrangements took advantage of available subsidies in 1998. This distribution problem has eased significantly in recent years. Yet several risk factors are associated with this pattern: 1) having an infant or young toddler, rather than a child age 3 or older; 2) coming from a Latino or Vietnamese-American community; 3) having spent less time on welfare; and 4) living in a neighborhood with fewer center-based enrollment slots. A companion PACE policy brief details how counties are pushing to creatively expand the use of childcare subsidies. WORKING PAPER SERIES 01-2 Child-Care Aid and Quality for California Families: Focusing on San Francisco and Santa Clara Counties August 2001 Bruce Fuller Yueh-Wen Chang Sawako Suzuki University of California, Berkeley Sharon Lynn Kagan Teachers College, Columbia University Yale University A Policy Analysis for California Education PACE Table Of contents wwwwss\\s w \\\\\~V \M \\ ‘\ Introduction What Types of Child Care are Mothers Selecting? \QEQ s‘\< Multiple Indicators of Child-Care Quality Shifting Policies to Aid Poor Families The Growing Up in Poverty Project Major Issues Organization of the Report JbMAAA Organizational Features Education Levels of Child-Care Providers Learning Materials and Facilities LOLOOUU‘l Child Activities and Verbal interaction Social Rules and Warmth Expressed between Child and Caregiver Mothers’ Assessments of their Child-Care Providers Providers' Beliefs and Commitments Do FCCHs and Kith—Kin Settings Differ? Which Mothers Utilize ChildCare Subsidies? wr‘ Lessons Learned and Local Policy Options Appendix 1 Endnotes Estimating Child-Care Subsidy Use Subsidy Use is Tied to Center Programs Risk Factors that Predict Non—use of Subsidies Estimating the Probability that Mothers Select Centers and Preschools The Good News Where Much Work Remains Conclusion ’I2 16 ’18 2O 2’] 22 22 23 23 25 26 26 27 28 29 30 » xv, "w .1 z. i -; ‘ : 1 ‘ - 5‘ _ ,x ,(mew _ . (A, y, n. .\- - -» ‘ . l‘ ‘ * ‘ « . ' :V: ’ 7‘ , ~ . \ . 4 V . 7‘ ‘ { ‘ , ‘ , . . A ’. . ' .n -_ \\ \\\\\\\\\\\\\\\\\\§\ \\\\\\\\\\\\\\\\‘\\ \\\\\\ \\\\\\\\\\\\\\ § §\\\\\ \ss \§\ \§ *\ Shifting Policies to Aid POOI“ Families In the summer of 1997, the California legislature decided to revamp the state’s family welfare program. Their action followed work- first experiments in other states, and then Presi- dent Clinton’s approval of federal welfare reforms in August 1996. In changing Califomia’s welfare requirements, the Sacra- mento policymakers imposed time limits on cash assistance and stiffer work requirements. For the first time. almost all single mothers with preschool-age children were required to enter a work activity once their infants reached the age of 6—12 months, with the exact age set by county—level officials. This remarkable shift in family policy also included stronger incentives for lower-income parents to stay in the workforce and off the welfare rolls—or to “make work pay” in Presi- dent Clinton’s words. In more limited ways, California governors Pete Wilson and Gray Davis followed suit by providing new state resources to aid working—poor families. During their administrations, the following initiatives have been undertaken: Child—care and preschool programs have been sharply expanded. “ A new child-care tax credit was created in 2000. Efforts to increase participation in child health insurance are under way. Policy leaders have pushed through an increase in the minimum wage. Against this backdrop of evolving policies, several empirical questions have come into focus. Each speaks to the direct experiences of the hundreds of thousands of single mothers and young children still enrolled in the state’s CaIWORKs program: x How are single mothers and their pre- school-age children faring as they move from cash aid to jobs? What kinds of child-care arrangements do mothers select and what levels of quality characterize these settings? \\ Which mothers are able to access child- care subsidies—either slots in centers or vouchers for home-based arrangements— and does this support bolster their employability? These questions are currently being inves— tigated by the Growing Up in Poverty Project. Originally a joint initiative involving scholars from UC Berkeley and Yale University, our expanded team now includes researchers at Stanford University and Teachers College, Columbia University. The Growing Up in Poverty Project In 1998 our field staff invited over 1,000 single mothers to join the GUP Project. These women shared two characteristics: each was entering a new state welfare program with a strong work—first emphasis, and each had at least one preschool—age child of 12—42 months at home. The Project recruited these families from five counties spread across three states: Califor— nia, Connecticut, and Florida. This paper reports on wave 1 data, col— lected in the second half of 1998, from the 410 participating mothers residing in San Francisco 1 or Santa Clara county. The entire three-state sample included 948 families during this first data collection period. Initial descriptive results were reported in our national report, Remember the Children, published in February, 2000. Each participating mother sat for an in-depth interview, lasting between 75 and 120 minutes. During the next four to six months, we kept in touch with each mother to see whether she selected a child-care provider while she responded to new work requirements under California’s reformed welfare program, dubbed CalWORKs.1 This was the second step in our data collection. In some cases, the mother retained a child-care provider that she had already been using— whether a center slot, a licensed family child- care home (FCCH), or a nearby kin member. The final step in the wave 1 exercise involved a half-day visit to each youngster’s child—care or preschool setting to assess its quality on a variety of indicators. Among the 410 California mothers, 259 (55%) did select a child-care provider for at least 10 hours per week within the six-month window for wave 1 data collection. We gained permission from the mother and provider to visit 216 of these 259 child—care settings. We also collected baseline measures of the children’s early language, cognitive, and social development. At wave 1 (in 1998) the median participating child was 2.5 years old. Table 1.1 displays selected attributes of the San Francisco and Santa Clara family samples. Sampled mothers, on average, were three years older than both counties’ total population of families with a preschool—age child. The San Francisco sample of mothers was predominately African-American, whereas the Santa Clara County sample was mainly comprised of Latino families. We purposefully oversampled Viet- namese-American families in Santa Clara County so we ‘54 an aid Q in prior year could look at this Comparisons are for eligible county-wide populations of clients: single mothers with preschool-age children in state TANF programs, 1997-1998. For Connecticut, the percentage of women on aid is for the year prior to random assignment. 2 San Francisco . th. Sample 29 57 ’l8 0 97 SUbgmuI’ 1“ dep Population 26 56 ”I6 3 92 . Major ISSUES San Jose . . . Sample 29 7 5’1 26 98 Part1c1pat1ng Population 26 ’11 51 15 NA mothers rely heavily Manchester . h'l _ Sample 26 2o 19 0 6O 0“ “Te” C 1 d we . Population 25 23 16 0 48 prov1ders. The med1an New Haven child participating in Sample 25 44 2’1 0 65 - Population 24 42 so 0 57 the GUP S‘Udy 1“ 1998 was spending 39 hours Tampa . . Sample 52 47 ’I4 ’I 92 per week With a child— Population 30 47 25 0 NA care provider (among those families using caregivers at least 10 hours per week). Child care continues to be viewed by state and local policymakers as a major support that can boost mothers’ ability to find and hold down a job. County governments in San Francisco and Santa Clara have invested new resources in child-care subsidies for welfare-poor families. State spending on child-care and preschool programs has climbed since 1996 from $800 million to $3.1 billion (including federal block— grant support).2 Welfare officials and child development activists in many counties have come together to help target new dollars on improving the quality of early childhood pro— grams. most recently aided by local children and family commissions (Proposition 10). Quality of Child Care Selected Evidence remains scarce, however, on the quality of child care being selected by lower- income families. Earlier research paints a mixed picture: the quality of center—based programs across middle-class and blue—collar communities is quite uneven and sometimes mediocre. Yet targeted subsidies supporting centers within poor neighborhoods, along with accompanying regulations. have sustained more adequate quality levels. Little is known empirically about the quality and character of home—based care arrangements.3 Additionally, little data has been available on the quality of care accessed by welfare-poor families as parents re—enter the labor force. This paper focuses first on the question of quality, reporting on multiple indicators for centers and home—based arrangements that were selected by mothers in San Francisco and Santa Clara counties. To provide comparative data on quality, we also observed 176 centers and family child—care homes (FCCHs) in the Bay Area and in Connecticut during 1997, including organiza- tions situated in middle-class and lower-income communities.4 We also reviewed earlier studies of quality that included California. Who is Able to Access Subsidized Care? The second issue we address in this paper relates to which mothers were able to access child-care subsidies during wave 1 data collec- tion in the second half of 1998. Our initial report (February 2000) indicated that just under half of all participating women were drawing child-care subsidies in the two counties combined. This percentage rose to 61% among mothers who had selected a child-care provider. For San Fran- cisco, we also are working with the Department of Human Services to verify each woman’s eligibility for child care, that is, whether she was engaged in a work activity or looking for a job. Our shared aim is to pin down baseline levels of subsidy use during the first year of the CalWORKs program. We will then track how mothers’ use of child—care subsidies changes over time. Wave 2 data collection with GUP families was completed in December 2000. Initial longitudinal findings, including changes in subsidy use, will be published in early 2002. Characteristics of Subsidy Users We also report on the characteristics of mothers and households that are associated with a greater probability of mothers using available child—care subsidies. Those factors that predict lower usage rates—for example, having younger children or belonging to certain ethnic groups— can be seen as risk factors that program managers and caseworkers might learn to recognize. Clients with these attributes are less likely to request child-care aid. One major finding is that the type and quality of child care selected by mothers has been linked to the use of subsidized care. In San Francisco, for instance, among those GUP participants who selected licensed care, 70% reported that this arrangement was fully subsi- dized. But among mothers using a home-based arrangement (either an FCCH or kith or kin member), only 19% were utilizing a child-care subsidy. In short, subsidized care remains tied to contracted slots in centers or preschools. Our qualitative substudy also reveals that when some women say, “day care,” they mean a center—based program. The tacit language used to describe formal center—based programs is linked to moth- ers’ propensity to seek the support that could boost their long-term employability. Organization OF the Report The following four sections of this report describe the study results in greater detail. In Section 2 we sketch the types of child care selected by participating mothers during wave 1 data collection. Section 3 turns to the issue of child—care quality. Here we address a variety of quality indicators based on data collected on centers and home—based providers in Santa Clara and San Francisco counties. We also include statistical estimates of maternal and household characteristics that help to predict the type of care that mothers selected. Section 4 focuses on the issue of subsidy use. First we describe subsidy use for different kinds of care and among different groups of mothers. Then we assess whether certain maternal or household factors reliably predict which women are using available subsidies. Section 5 summarizes lessons learned and policy options for local and state policymakers that stem from these findings. 4 ‘ ,--~ . . it: >me sews " ax...- $1238 \M§@§§ What Types of Child care Are Mothers Selecting? First we looked at the kinds of child care selected by mothers participating in the full three-state family sample and compared it to patterns in San Francisco and Santa Clara counties. Figure 2.1 shows the percentages of mothers who were able to access the three major forms of care—centers or preschools, FCCHs, and unregulated kith and kin members—for each of the GUP Project states. During their initial interview, about 29% of all mothers with child care in the two sampled California counties (San Francisco and Santa Clara combined) selected a center-based program. This compares to 70% of the Tampa, Florida participants, and just 13% of sampled mothers in our two Connecticut counties (Manchester and New Haven).5 The use of FCCHs was significantly greater in the two California counties, equaling 17% of all FigUre 2.1. Type of child-care providers by state c1) 0 / 1:::/ /:::f:7 C:_:7 g 100/0 . 54% N 77% 25% u_ ‘ l i ‘ ‘- I O U) (D E *4 BOO/(r r E C . 8 ‘9 . U 1 o\° 0%; - . California Connecticut Florida n=262 n=168 n=140 H: Unregulated kith & kin care I Family child—care homes families, compared to just 10% and 5% in Connecticut and Florida, respectively. In San Francisco and Santa Clara counties, we see differing child-care selection patterns. Figure 2.2 provides this breakdown between two and six months after the initial maternal interview. Among San Francisco mothers, 51 selected a center—based program (44% of the San Francisco subsample), compared to 27 of the Santa Clara mothers (28%). Women in Santa Clara County were more likely to use FCCHs, a total of 27 participating families (22%), compared to 17 San Francisco families (15%). The type of child care selected holds implications for the quality of young children’s daily settings and for the flow of subsidies that makes care affordable for lower-income families. N§WNWWWWWW§Y@WX v:.~ \ \ ‘ N. \\3 so \\ \ W‘ an immune Indicators of Child-Care Quality We turn next to the question of quality, including how the quality and character of center versus home—based care differs between the two California counties. Little empirical evidence has yet to emerge on the quality of child care that welfare-poor women are able to access, particularly those with young children who rarely faced the stiff work requirements enacted in 1997. We earlier estimated that, between 1996 and 1999, at least one million additional child-care places for preschool-age children were required for families facing new work requirements or for single mothers leaving the welfare rolls.6 But little has been known about the type and quality of these child—care settings. This section details various indicators of quality for the child-care settings mothers selected in San Fran— cisco and Santa Clara Figure 2.2. Types of child care selected'bv mothers by county 80/ 7O~ (SO 50- x42 409 so- 2o~ Counts of children 10C I, 2;: San Francisco I Children, 12-23 mos. I Children, 24-42 mos. 5V ,:::T::: 1 Center FCCH Kith & Kin Center Santa Clara counties. These data were collected during our initial maternal interview, a half-day observation of the 216 providers that we were allowed to visit, and an interview of each provider lasting about 45 minutes. We collected data on the following I FCCH Kith & Kin indicators of quality: Distribution of types of child care is statistically significant (p < .O’l) between the counties. xx Organizational features. These included the number of children in the focal child's classroom or home-based setting, and the child-to-adult ratio in the setting. Education levels and demographic features of child-care providers. This included the provider’s school attain- ment. training in child development, ethnic membership. experience. and age. Availability of age-appropriate learning materials, resources for play, and the quality and safety of facilities. These measures are embedded in the Early Childhood Environment Rating Scale (ECERS) for centers, and the Family Day Care Rating Scale (FDCRS) for all home- based settings. Children’s activities and verbal interaction. We observed the focal child’s engagement in activities and social interactions with other children and adults, during 40 timed snapshots. Social rules and warmth expressed between child and provider. Summary scales were constructed that gauged the warmth. responsiveness, and supportive character of the main adult caregiver (independent of the focus child), including the degree to which the adult verbally explains things to the child. Mothers’ assessments of their child- care providers. We asked each mother a variety of ques— tions about their main provider, including the flexibility of hours, how happy and safe they believe their child to be, and whether the provider was open to the mother’s feedback and ideas. \ Child-care provider’s views and commitments. During the interview with each provider, we asked several questions regarding her or his commitment to the care-giving role, the nature of communication with the mother, and beliefs about child rearing. organizational Features Certain attributes of centers and home- based settings are related to healthy child devel- opment. These factors include the ratio of children per adult in the setting, overall group size, the caregiver’s education level, and the availability of appropriate play and learning materials.7 During our visit to each provider, we recorded the number of children and adults in the child—care setting. Figure 3.1 reports the average number of children in settings by type. Mean enrollments were slightly higher in San Francisco centers (15.4 children), compared to Figure 3.1. Mean child group sizes Number of children San Francisco Santa Clara I Centerm : FCCl—l: 7: Kith & Kin Differences in means are not statistically significant between counties. Sample sizes for Centers, FCCH, and Kith & Kin are 31, ’14, 26, in San Francisco and 29, 43, 35 in Santa Clara, respectively. §§Z§§ T§§ Multiple Gauges of Child-Care Quality Parents and professionals alike use many of the same criteria to define the quality of child care, regardless of whether it is provided at centers and preschools or in home settings. As discussed in the text, some of these have been empirically correlated to growth in children's development over time. To capture different facets of quality in centers and home settings, we employed the following measures: The teacher's or caregiver's own attributes These can be influential predictors of youngsters’ early growth and learning. One frequently used attribute is the provider's own school attainment level. We also asked teachers and home—based caregivers about motivational factors, including their commitment to offer child- care services, their feelings of satisfaction from doing this work, and their desire for more training. Organizational factors Certain aspects of the child-care organization have been related to children’s early development. The child‘staff ratio, or number of children per adult in the setting, is a regulated indicator of quality. Sometimes researchers also look at the maximum number of children that are in the classroom or home setting, since this may indicate how much individual attention and care youngsters receive from adults. The Early Childhood Environmental Rating Scale (ECERS) This widely used observational instrument assesses a range of variables at child-care centers, including the availability of reading and learning materials, age-appropriate tasks and projects, the organization and cleanliness of facilities, outdoor play materials, and the warmth and responsiveness of staff members. The FDCRS is a parallel observational instrument that captures quality along the same dimensions and is used in home-based child-care settings. The Child caregiver Observation System (C-COS) Observers use this measurement scale to record information about the activities and language interactions that the focal child has with adults and other kids in the child-care setting. Developed for the national evaluation of Early Head Start, the researcher typically observes for 40-50 short-time intervals, recording in detail what the focal child is doing and with whom she or he is interacting. The Arnett Scale of Caregiver Behavior (Arnett) This scale focuses on the teacher or adult caregiver. It gauges the kind of affect, support, and language that occurs between the adult and children in the child—care setting. When 0UP researchers analyzed this instrument, they found that it tapped into the adults‘ responsiveness and warmth.1 It also measured the extent to which caregivers reason with children about problems or activities, rather than being more directive and simply telling them what to do. 1These relationships among the quality indicators stem from our observations in 175 centers and 203 home-based settings, along with interviews of each participating child's teacher or caregiver For this particular analysis, we combined regulated FCCHs and kith or kin arrangements. These child—care settings are spread across California, Connecticut, and Florida, See Fuiler, Kagan, et al. (2000) for details. All relationships reported are statistically significant at the p < .05 level or higher Santa Clara County centers (14.5 children). Group size in FCCHs was much higher in San Francisco on average, relative to Santa Clara County, 6.5 versus 3.6 children. GUP Project families in Santa Clara County utilized FCCHs at twice the rate of families in San Francisco. Within informal settings, where kith or kin members provide care, between 2—3 children are present on average in each county. Figure 3.2 displays the distribution of group size for centers in each county. The horizontal lines indicate median group sizes among all centers selected by GUP mothers. Half of all values are centered around this median and indicated by the upper and lower bounds of the box. As Figure 3.2 vividly shows, a significant number of youngsters are spending their days in quite large groups or classrooms of 15 or more children. Figures 3.3 and 3.4 display mean group sizes for each county, splitting children into the younger (ages 12—23 months at wave 1) and older (24—42 months) cohorts. As one might expect. group sizes in centers were larger for the older group, compared to the Figure 5.2. Distribution of child group sizes for centers 40 (N C? A C? Number of children M o N= '30 29 San Francisco Santa Clara Difference in means is not statistically significant. 0 reported in Figure 3.5. Smaller ratios are gener- ally preferred, since they are associated with more positive child-development outcomes. San Francisco centers displayed a smaller mean ratio (4.511), compared to Santa Clara County centers (5.911), despite the fact that group size tended to be higher in San Francisco centers (as seen above). The average child~to—staff ratio is a bit higher in San Francisco FCCHs (2.5:1), relative to those in Santa Clara County (2.1 :1) younger group. In center-based programs, group sizes for the younger group tend to be lower in 1: Santa Clara, relative to San Fran- E) 14— cisco. For children in FCCHs, E ’12“ group sizes were considerably “:5) 10— higher in San Francisco among the g :35: older group, compared to Santa é 4~ Clara FCCHs. 2- We then took into account the 07— observed number of adults in each Center FCCH :77,My”."Children,“i2-245mos. Figure 3.3. Mean child group sizes (San Francisco) \ Kith & Kin C Children,7724-42 mos. child—care setting and calculated the ratio of children per adult caregiver. These average ratios are 8 Sample sizes for Center, FCCH, and Kith & Kin are 6, 5, ’ii for the younger group and 25, ii, ’15 for the older group, respectively. Figure 3.4. Mean child group sizes (Santa Clara) 18—” 16‘ @144 A _\ O l\.) l 1 Number of child Center FCCH i ‘ candies, 3727273 as. ’ Sample sizes for Center, FCCH, and Kith & Kin are 4, 15, 16 for the younger group and 25, 28, 19 for the older group, respectively. Again, it‘s instructive to split participating GUP children into the younger and older age groups (Figures 3.6 and 3.7). Within center— based programs, the mean child—to-staff ratio is higher in Santa Clara County (62:1) for the older group compared to San Francisco (4.721). But this staffing ratio is essentially equal be— tween the counties for the younger child group. The staffing ratio within FCCHs serving the older group is higher in San Francisco than Santa Clara. Figure 3.8 illustrates the range of child—to— staff ratios for centers in each county. Again we see that many participating children are placed in centers with quite high ratios. The median ratio is indicated by the horizontal line within each box. The box marks the range between the values at the 25‘h and 75‘h percentiles. The maximum child-to—staff ratio allowed for state subsidized centers is 8:1. Several centers exceed this quality standard. Education Levels of Child-Care Providers The cognitive growth of young children tends to rise more steadily when they are cared Kith & Kin children, 24-42 mos. if j for by more highly educated adults. This is not necessarily true in other areas of development, such as social development or the acquisition of cultural knowledge. Figure 3.9 reports the percentage of providers having completed high school by child-care type. Over 90% of center teachers reported having completed high school. In contrast, among kith and kin provid- ers, 73% in San Francisco and just 41% in Santa Clara County had received a high school diploma. Learning Materials and Facilities To gauge the availability of learning— related materials and the character of physical facilities, we administered the ECERS measure- ment tool (for centers) and the corresponding FDCRS instrument (for FCCHs and other home- based settings). We used about 15 individual scales from each instrument. ECERS Results for Centers The ECERS broke down into reliable gauges of two distinct dimensions of center Figure 3.5. Childzadult ratios Mean ratio Santa Clara San Francisco L¥FCCHV : Kith & Kiri I Center Differences in means are not statistically significant between counties. Sample sizes for Center, FCCH, and Kith & Kin are 31, 12, 26, in San Francisco and 29, 43, 55 in Santa Clara, respectively. Figure 3.6. Child:adult ratios (San Francisco) 7_/ Mean ratio Center FCCH Kith & Kin I Children, 12-23 mos. Children, 24—42 mos. Sample sizes For Center, FCCH, and Kith & Kin are 6, 3, 11 for the younger group and 25, 9, ’15 for the older group, FESDGCthBIV. quality. The first cluster included measures related to the availability of learning materials quallty (books. play and crafts materials, educational encouraging children to speak and interact verbally. Centers in both counties had an ample supply of play and learning materials (Figure 3.11). These individual ECERS measures correlated consistently to high-quality learning activities and facilities at centers (Figure 3.12). We also can compare across individual ECERS item scores to identify the facets of center quality that should receive the most atten- tion. Appendix 1 lists individual items by county. This analysis indicates that shortcomings in are apparent in the following areas: Center teachers’ and aides’ language work videos). to teachers engaged in learning activi— With children through reading practice and ties. and to responsive interaction with chil— talk that advances children’s reasoning dren.8 A second set of items related to the and problem-solving skills (in 5311 character of facilities. space for gross motor Francisco). play (indoor or outdoor). and furnishings for s Health practices and sanitary conditions to play and crafts activities. This second cluster cut down the spread of germs. such as appeared to operate somewhat independently of the first. We first report on specific ele— ments of these indices. Then. we report Figure 3.7. Child:adult ratios (Santa Clara) on how centers varied on these two 7— .\\\\\ composite indices. Finally. we repeat (55— : ‘ this presentation for FCCHs and kith g _ and kin settings. drawing on the g 4 FDCRS gauge of quality. For example. g 3“ \\\\\\\\\ Figure 3.10 shows that centers in San 2‘ § * Francisco had a moderate number of 1:ng f § children's books. with Santa Clara 01 Centerpw County WI having a somewhat “i"‘crlaien, a*2:23'nagsf“"ij’aaldaa, 24:52 535;? ‘ stronger supply. Center teachers in . Sample sizes for Center, FCCH, and Kith & Kin are 4, 15, 16 for Santa Clara County scored quite high in the younger group and 25, 28, 19 for the older group, respectively. 1 O Figure 3.8. Distribution of childzaduit ratios for centers 15 10- Childzadult ratio -S I l San Francisco Santa Clara Difference in means is not statistically significant. handwashing (in San Francisco, and to a lesser extent in Santa Clara County). Possible over use of the television and non—educational videos (in Santa Clara and San Francisco counties). FDCRS Results for Home-based Settings The FDCRS rating scale is quite similar to the ECERS, but is better adapted to home—based child—care settings. The FDCRS assumes that these settings offer materials and activities appropriate for preschool-aged children. FDCRS item scores are low overall (e.g., Figure Figure 3.9. Percentage of providers who have completed high school 100— j 80- 60— _ Santa Clara :kith & Kin San Francisco l Center 7 Z FCCH The distribution of differences among the types of care is significant (p<.OOO’I ). Sample sizes for San Francisco and Santa Clara are 76 and 147, respectively. 3.13), and findings were similar between FCCHs and kith and kin settings in both coun- ties—with two important exceptions. In San Francisco, FCCH providers encouraged children to be more verbal and used more balanced discipline strategies compared to kith and kin providers (Figures 3.13 and 3.15). In Santa Clara County, FCCH providers displayed more Figure 3.10. Quality (ECERS) scores for children's books and encouraging chfldlanguage Mean SCOFGS (N J? U1 A l i Santa Clara San Francisco l _ I Books Language l Sample sizes for books and language items are 28 for centers in San Francisco, and 30 in Santa Clara. positive affect and emotional tone, and more balanced discipline than kith and kin providers (Figure 3.16). We can place ECERS and FDCRS scores for the two counties in a broader national con- text by looking at mean summary scores. Figure 3.19 shows the average item score on the ECERS for centers that were selected by partici— pating mothers in each of the three GUP states. Quality at San Francisco and Santa Clara County centers is relatively high, compared to mean ECERS scores for centers in Connecticut and Florida. Equally important, two earlier observational studies in a wider range of Bay Area communities put average ECERS scores at 11 Figure 3.11. Quality (ECERS) scores for materials related to learning and motor skills Mean SCOF es T‘N’WFWOPT' O _| San Francisco Santa Clara L“- Plav &rlearningg__ Gross._m0t9r i Sample sizes for play and learning, gross motor items are 28 for centers in San Francisco and 30 in Santa Clara, respectively. 4.3 across all items, compared to 5.2 (out of 7 points maximum) for centers in the GUP sample. This means that GUP Project mothers were able to access centers of relatively strong quality in the context of the wider market of center—based programs. Figure 3.20 reports similar comparisons for home—based settings. For the GUP family sample we found only the few differences Figure 3.12. Two quality (ECERS) indices: structured learning activities and facilities and furnishings Mean scores 1? Santa Clara San Francisco I Learning activities L? Faculties & furnishings l Sample sizes for learning activities and facilities and furnishings indices are 25 for centers in San Francisco and 29 in Santa Clara, respectively. 12 between FCCHs and kith or kin arrangements, so they have been combined in this figure. There are two notable findings here. First, the overall quality of home-based settings for participating GUP children across the three states is low, with the mean item score falling at or below the mediocre level. Home-based settings in the two California counties displayed equally low quality, compared to those in Connecticut and Florida. Second, the quality of home-based settings selected by GUP mothers Figure 3.13. San Francisco quality (FDCRS) scores for encouraging child language and presence of materials and manipulatives Mean scores 4? l l l l Materials _L:Klth & Kin-m Language I FCCH Sample sizes for FCCH and Kith & Kin are 11, 17 for Language item and 13, 24 for Materials item. was of significantly lower quality on average, at least on the FDCRS scale, compared to the settings we observed in a wider range of Bay Area communities.9 Child Activities and Verbal Interaction A direct measure of the activities and tasks in which children are engaged—one that quanti— fies the frequency and form of adult—child interaction—was recently developed by research— ers at Mathematica Policy Research in Princeton. This instrument, called the Child—Caregiver Observation System (C—COS), also is being Figure 3.14. Santa Clara quality (FDCRS) scores for encouraging child language and presence of materials and manipulatives Mean scores Materials Efi?“ “Dial Sample sizes for FCCH and Kith & Kin are 40, 31 for Language item and 39, 34 for Materials item. used in the national evaluation of Early Head Start. It allows the observer to record exactly what the focal child is doing during 40 timed snapshots, each lasting 30 seconds. Figure 3.21 illustrates the kind of informa— tion the C—COS yields. It combines observations from all three participating GUP states. For instance, the first pair of vertical bars (far left) shows that we observed the focal child in centers asking the teacher or aide a question in 10% of the 40 possible snapshots. In home-based Figure 3.15. San Francisco quality (FDCRS) scores for child-caregiver tone and balanced discipline 7% Mean SCOFES Tone Discipline I FCCH C Kith & Kin ,. _- ,, ,,_, 7_7*7 Wtd Sample sizes for FCCH and Kith & Kin are 12, 24 for Tone item and 13, 24 for Discipline item. Figure 3.16. Santa Clara quality (FDCRS) scores for child—caregiver tone and balanced discipline Mean scores 4? Tone Discipline l _!_FCCH Kith & Kin i Sample sizes for FCCH and Kith & Kin are 41, 34 for tone item and 40, 34 for discipline item. settings, however, the frequency of child queries was more than double this, or 22% of the 40 snapshots. We know little about the content or richness of these verbal interactions. But it does suggest that focal children in home-based settings produce more language with their providers. Reading—related behavior was observed infrequently in both types of settings, only 3% in centers and 2% in homes. Focal children were engaged with materials almost two-thirds of the Figure 3.17. San Francisco two quality (FDCRS) indices by care type Mean SCOFBS Learning Activities Discipline Kith & Kin _l FCCH Sample sizes for FCCH and Kith & Kin are 10, 12 for learning activities index and 11, 23 for discipline index. 13 time. They interacted with other children in center settings 44% of the time, as compared to 19% of the time in home—based settings, where they were also observed watching television almost one-fifth of the time (18%). The next two figures replicate the previous graph for San Francisco and Santa Clara coun- ties. Figure 3.22 presents the findings for cen- ters, while Figure 3.23 presents those for home- based settings (combining FCCHs and kith and kin). In both settings, children spent consider— able time working with learning or play materi- als. They spent more time watching television in home—based settings, compared to centers. Figure 3.18. Santa Clara two quality (FDCRS) indices by care type Mean scores 4? Learning Activities Discipline ———fi I FCCH L Kith & Kin Sample sizes for FCCH and Kith & Kin are 57, 27 for learning activities index and 35, 27 for discipline index. Providers in homes tend to ask children more direct questions. No significant differences were found between counties. There was considerable variation in child— adult interaction within center- and home-based settings. 3.24 illustrates the wide range in the frequency with which caregivers asked ques— tions of children. The horizontal line in each box indicates the mean count of snapshots in which provider queries were observed. The box demarcates the range of values falling between 14 Figure 3.19. Mean ECERS scores for GUP centers and from two earlier studies. 7'/ Quality Index Florida Connecticut California Average center quality l I Centers serving CUP Project children i . 3 Centers serving wider range of families l (based on two prior national studies) the 25‘h and 75‘h percentiles. The outer horizon- tal lines, appearing above and below the box, indicate the entire range of values observed from the lowest to the highest value. Figure 3.25 shows the variability in the frequency with which the focal child was ob— served interacting with at least one other child. The differences correspond to the variation in Figure 3.20. Mean FDCRS scores for GUP family child-care homes and from one earlier study 7- Quality index Connecticut California Florida Average FCCH quality i FCCHs serving CUP Project children FCCHs serving wider range of families (based on one prior national study), i l l Figure 3.21. Percentage of time children are engaged in various activities (three states) 707/ 50* 20- % of observation time ’IO- Provider Provider Child Interacting Child Child asks child reading with interacting with other watching TV unoccupied a question child with materials children : A ,4 :77, A :, 7 ":4 ,7:::,,: _ A ,, :7,:::____. I Children in centers E Children in home-based care . Percentages are for 40 timed observation snapshots. Center and home-based settings in California, Connecticut, and Florida. N=158 centers and 136 home-based settings (FCCH and Kith & Kin). Figure 3.22. Percentage of time children are engaged in various activities (San Francisco) 7O- : . 60- 66.0 ‘1’ E 50—. i C i .9 . *5; 40— l a : i g 30‘ i O . ”5 20~ o\‘3 ’IO~ 0—1 5 ' V i :: Provider Child Child Child asking child interacting watching TV unoccupied a question with materials I Center I FCCH :7 Kith & Kin ‘ Percentages are for 40 timed observation snapshots. Difference in means is statistically significant between child-care settings for "Child watching TV" (p < .01 ). Sample sizes are for Center, FCCH, and Kith & Kin are SO, 11, 23, respectively. 15 Figure 3.23. Percentage of time children are engaged in various activities (Santa Clara) 70- 60- 50- 40- 30- 20- % of observation time 10- Provider Child asking child interacting a question with materials Child Child watching TV unoccupied I Center w FCCH : Kith & Kin Percentages are for 40 timed observation snapshots. Differences in means are statistically significant between child-care settings for "Provider asking question" (p < .01) and "Child watching TV" (p < .01). Sample sizes for Center, FCCH, and Kith & Kin are 30, 43, 33, respectively. group sizes reported above for the three types of child care. That is, focal children in centers interacted with other youngsters more fre— quently, compared to children in home—based settings where group sizes were much smaller. A final way we measured child-adult interactions was to analyze the groupings of individual items on the C-COS, similar to the principal components procedure we ran on the ECERS and FDCRS items. For centers, the 22 individual items on the C-COS clustered around three basic factors: verbal interaction between the focal child and caregiver (also correlated with the child’s warm and positive affect); lateral interaction between the focal child and other youngsters in the setting; and \ interaction between adult caregivers. 16 These interaction patterns may distinguish center classrooms that contain a teacher and aide, or instances where child groups are com- bined for certain activities. In Figure 3.26 we illustrate one dimension—oral language be- tween the focal child and caregiver—and plot index scores for centers selected by GUP Project mothers. It shows slightly higher observed talk among children in Santa Clara County centers, compared to San Francisco. Social Rules and Warmth Expressed between Child and Caregiver At the end of each observation period, the field researcher completed a set of 26 rated items. These related to how the caregiver—a center teacher, FCCH provider, or individual kith or kin member—interacted with children in the setting. This measure, known as the Arnett Figure 3.24. Caregiver asks child a question or requests child to talk (both counties) .b O LN C? A C? O Informal Number of snapshots (max 40) I\) 0 Centers FCCHs Figure 3.25. Frequency with which focal child interacts with another child (both counties) 550 Owow Mothers using subsidy Mothers not using subsidy Difference in means is statistically significant (p<.OO’l for 259 mothers) 23 §\\ \ . . & \§ s‘ k 8‘} s “\‘xk Which parents are less likely to draw child-care aid? 3 Parents from immigrant communities, including Latina and Vietnamese mothers, who may not speak English fluently. s Parents with children under 3 years old who believe that subsidies are fused to center-based programs, unaware of the options available with child-care vouchers. a Parents with stronger support networks who often find a kin member to provide child care, losing out on voucher support. a Parents with no prior experience with welfare or center—based child care, those with the least knowledge of subsidy options. R Parents who live in lower middle-income neighborhoods with a scarcity of centers and family child-care homes. precisely understand why this difference arises. Other indicators of social support suggest that women with higher levels of support from household members and others are less likely to use center- based care or draw subsi- dies. The number of co- residents in the mother’s household could be related. Community poverty women are more likely to be drawing subsidies than any other ethnic group, but this difference is of marginal statistical significance. It is difficult to judge whether reliance on informal, often unsubsidized child care yields negative effects on children’s development, especially for recent immigrant groups, such as the Vietnamese-American families in Santa Clara County. Early learning and socialization always occurs in particular cultural settings. When centers and preschools are scarce or can not match parents” language and cultural norms, informal care arrangements may yield better child outcomes. Much more research is needed to inform this important question. AdUIt social support Women who live with no other adult are almost twice as likely to access child-care subsidies, compared to those who live with one or more adults. Figure 4.3 displays this differ- ence: 29% of those mothers using subsidies live alone, whereas just 17% of women not tapping their child-care subsidy live alone. We don’t 24 Mothers who live in more impoverished census tracts are more likely to draw a child—care subsidy. Figure 4.4 shows that the incidence of poverty is a bit higher among women using subsidies (30% of all children in their census tracts were below the poverty line), relative to the poverty level in the tracts in which non-subsidy users lived (25% of all children in poverty). This may be related to the fact that subsidy use is stronger when cen- ters are more available. This has been observed in poorer census tracts in both San Francisco and Santa Clara counties. Among subsidy users, Figure 4.3. Percentage of mothers who live with no other adult by subsidy status 50y g 2549 :3 g 20— % mothers living with he 3:1 “WMothers not using subsidy Mothers using subsidy Difference in means is statistically significant (p<.O2 for 259 mothers) Figure 4.4. Share of children living below the poverty line in mothers' census tracts by subsidy status 30f 4325‘. s l» 1-3201} 8 E1 4-2 1‘ inm i % children in poverty Mothers not using subsidy Mean difference is statistically significant (p<.04 for 255 mothers) Mothers using subsidy there were 571 child slots in centers (and 12 centers) within a one-mile radius of the median mother. This compares to 507 slots (and 10 centers) within the same area among women not using subsidies. This is consistent with other findings showing that women of slightly higher economic means—in blue-collar or lower middle—class communities—face scarcer sup- plies of licensed care.11 It’s also useful to note that mothers with just one child are less likely to use their sub- sidy than those with more than one child, a difference of 12% between subsidy users and non—users. With more children, and older tod- dlers or preschoolers, mothers are more likely to use center-based programs and more likely to use subsidies. Additional characteristics distinguish mothers who use child-care subsidies from those who do not. However, none of these reach statistical significance, so they should be interpreted cautiously. For example, women with slightly older children are slightly more likely to use their subsidy. No differences were found in rates of subsidy use between Latina and non—Latina mothers, between mothers who had recently attended a job club, or for those with higher school attain- ment levels. The findings on subsidy use presented in this section could have a very practical applica- tion if front—line caseworkers would be willing to look out for these risk factors in their clients. Providing special counseling or follow—up by child-care agencies that allocate subsidies could reduce the under utilization of subsidies. This is particularly true for the share of women using kith and kin caregivers who fail to draw voucher support. Estimating the Probability that Mothers Select Centers and Preschools Can we predict which mothers are more likely to select licensed child—care providers, including centers and FCCHs? The short answer is, yes, but only with a modest degree of cer- tainty. Given that most mothers who use subsi- dies do so in center—based programs, estimating which families benefit from centers or from subsidies yields very similar results. In a related GUP paper, we have estimated the likelihood that mothers will select a licensed provider (center or FCCH) rather than a kith or kin caregiver.12 The results are quite similar to the differences described above. This earlier paper included the Florida and California samples, so the results vary a bit. Mothers with younger children (under 30 months), more adults in the household, and stronger social support networks are less likely to select center- based programs. In addition, this analysis revealed that Latina mothers were less likely to access centers, as were Asian-American women. We also found that mothers who have spent fewer months on welfare were more likely to 25 select licensed care, compared to women who had been more steady welfare clients in the prior year. The influence of center capacity in these women’s immediate neighborhoods is strong when determining the likelihood that they select licensed care. When pooling all participating mothers across the three state samples, we discovered a significant relationship between the number of centers (and child slots) within a mile radius of each woman’s home and her own propensity to select a center or preschool. This demonstrates that not only maternal or family- level factors influence the use of licensed care: the community-level availability of centers appears to condition mothers’ own decision making as well. LESSOI‘IS Learned and Local POIiCV Options This analysis has revealed good news about the state of child-care centers in two Bay Area counties. It also has identified weaknesses in the quality of many home-based settings and within the broader child-care subsidy system— persisting gaps that local policymakers might address in the future. In some cases, officials in San Francisco and Santa Clara County are already mounting ameliorative programs. The 000d News Center quality is relatively high The majority of single mothers who selected a center-based provider—as they moved from welfare to work—were able to 26 place their child in a center of reasonable to strong quality. This is very good news for those poor families who are able to access centers and preschools. Multiple indicators of quality revealed generally high levels in San Francisco and Santa Clara County. Earlier research has shown that per capita supply of center-based care is signifi- cantly higher in San Francisco. Careful growth of supply in Santa Clara has not kept pace with child population growth. But this may contrib- ute to higher quality. Centers and preschools in this county show the strongest quality across all five counties involved in the GUP study nation- wide. More research is required to illuminate local policies that explain this mixed news. Mothers are attracted to certain features of home-based arrangements Women participating in the GUP study consistently reported that home-based arrangements—primarily kith and kin provid- ers—were more flexible in their hours, in closer touch with the mother, and provided more individual attention for their child, compared to mothers commenting on their center-based programs. When we interviewed providers at kith and kin and FCCH facilities, they re— ported that the mothers were generally hap- pier with the care they provided, compared to reports from center teachers about their clients’ satisfaction. How can centers and preschools be em— powered to incorporate these attractive features? Directors, for example, understand that many lower-income mothers work irregular shifts. But staying open in the evenings may boost staffing costs beyond what current reimbursement levels cover. An important policy discussion could be sparked by these findings: state and local offi- cials might learn from mothers’ positive views of home-based arrangements and support incen- tives that enable centers to follow suit. More mothers using home-based care are drawing financial aid More parents now receive child-care vouchers and exercise a wide array of choices than we observed in 1998. Both counties have made progress in raising the share of mothers who take—up their subsidy—presumably leading to more stable arrangements. More research is needed to understand how subsidy use actually is related to stability and quality of care. A related issue is whether the overall child-care system encourages informed choice. Historically, subsidies have been institutionally tied to slots in centers and preschools for wel— fare—poor families. In 1998, for example, 80% of the GUP mothers who failed to draw a child— care subsidy of any kind (inside or outside CalWORKs) were using kith or kin caregivers. Ideally, more parents could effectively use vouchers to reimburse their home-based provid— ers, especially in light of long waiting lists for center slots and scarcities of infant care. The good news is that an increasing share of parents who select home-based providers are drawing their voucher support, at least for a short duration of time. Since 1998 many more families have been utilizing child— care vouchers to reimburse kith and kin members, especially in San Francisco where the linkage between subsidies and center slots is becoming decoupled. Last fiscal year (2000—2001), 57% of CalWORKs clients receiving child-care aid through the welfare system used their voucher to reimburse a kith or kin member, equaling $12.3 million in reimbursements to caregivers. Child-care subsidy use is rising, compared to earlier levels Among mothers who reported using a child—care provider at least 10 hours per week, 61% reported some kind of public support for this arrangement. Based on data across the two counties, the great majority of these women (70%) had found a spot within a center-based program. It appears that county outreach efforts and more intensive case management are responsible for this increased use of child-care services. Where WOI‘k Remains While many of our findings suggest positive trends in child-care services, weak- nesses in the system still persist. Clarifying where work remains is essential as county and state policymakers address program priorities in the coming years. Focusing resources on particular facets of center quality While the overall quality of center—based programs is reasonably strong, some centers displayed specific weaknesses. In several centers the ratio of children per staff member is high, and exceeds the recommended quality standard of 8:1. In both counties, our observa— tions using the ECERS scales revealed the need for staff to read more with children, to make language materials more readily accessible, and to ensure higher quality facilities . Center staff could also become more skillful at helping children develop reasoning and problem—solving skills. The strengths of home—based providers—— flexible hours, open communication, and greater trust—offer additional lessons for center 27 directors and teachers. Centers and preschools will require stronger support and incentives to make these advances. Addressing the quality of home- based settings The supply of kith and kin providers is quite fluid, and they are often difficult to engage over time. This complicates efforts to improve the quality of their care. It may be possible, however, to reach such providers through targeted information campaigns or training efforts that encourage basic improve- ments in their caregiving, such as reading more to their children and relying less on television viewing. Both counties have under— taken efforts to improve the quality of home- based providers. Taking into account "risk factors " that mitigate against subsidy use Our analysis identified characteristics of mothers and families that are associated with a lower use of child-care support. These include parents from immigrant communities with limited English proficiency; parents of children under 3 years of age; mothers with stronger support networks; those with no prior experi— ence with center-based programs; and those who live in slightly better neighborhoods where the supply of centers is lower, compared to very poor communities. If caseworkers became more attuned to these client attributes. they could take extra time and offer more intensive follow—up to ensure that eligible women do use their child-care subsidy. Both counties have pushed to hire caseworkers with strong roots in diverse com— munities. We must continue to recognize that 28 the scarcity of centers and FCCHs continues to limit real choice and thus the motivation felt by parents to take-up their child-care aid. The policy dilemma is whether the shift toward public support of unregulated care is wise, given its uneven quality, and whether it detracts from building a stronger center-based infrastructure for working families. At the same time, as long as mothers see kith and kin (and FCCHs) as more responsive to their irregular work hours and their children’s socialization needs, demand for exempt care will continue to be strong. COI‘ICIUSiOfl In summary, this analysis yields a feeling of optimism on one score: the work of many people inside and outside of local and state governments, over the past 35 years, has led to a robust network of centers and preschools that displays quite high quality. This, despite the fact that they are situated in quite poor neighbor- hoods. In addition, county welfare and local child—care agencies have greatly improved their capacity to distribute financial aid for child care, both to families selecting centers and to many parents using kith and kin arrangements. The challenge now is how to build from these successes—especially as local officials and neighborhood activists seek to expand the capacity of centers and improve quality—and how to ensure more equitable quality for those families selecting home—based care. §W§NWWEWWWRWQ&&WW&§MWW§W®W\§&W§WW§t .3<-i\3;‘ \ APPENDIX 1 ECERS items for San Francisco Centers and Preschools ITEMS EC2 EC4 EC7 EC8 EC12 EC13 EC14 EC15 EC16 EC17 EC19 EC27 EC30 EC31 E032 Furnishings Play arrangements Outdoor play Equipment Sanitary/toileting Health practices Safety practices Language/books Child communications Language & reasoning Manipulatives Video use & complexity Teacher responsiveness Discipline practices Teacher warmth SAMPLE 28 27 28 27 28 27 28 28 28 28 28 13 27 28 28 MEAN STD. DEVIATION 6.14 1.35 5.59 1.80 4.96 1.55 5.33 1.75 4.68 2.13 4.48 1.91 4.86 1.99 4.11 1.45 4.54 1.79 3.25 1.55 5.18 1.83 3.85 1.72 4.52 1.53 5.04 1.53 5.25 2.03 ECERS items For Santa Clara County Centers and Preschools ITEMS EC2 EC4 EC7 EC8 EC12 EC13 EC14 EC15 EC16 EC17 EC19 EC27 EC30 EC31 EC32 Furnishings Play arrangements Outdoor play Equipment Sanitary/toileting Health practices Safety practices Language/books Child communications Language & reasoning Manipulatives Video use & complexity Teacher responsiveness Discipline practices Teacher warmth SAMPLE 30 30 29 29 30 30 30 30 29 29 30 23 30 28 27 MEAN STD. DEVIATION 6.57 1.17 6.17 1.37 6.34 1.04 6.69 .71 5.23 2.10 5.90 1.86 5.93 1.74 5.47 1.81 6.24 1.12 6.10 1.32 5.87 1.76 4.61 1.85 6.10 1.40 5.93 1.46 6.70 .82 29 , §§\\\\§s\\\§§\\s§\\ \\ m \a \\ \ \\ sass“. h... 1 The California legislature, when enacting its version of welfare reform, recognized the new exigencies facing children by renaming the old AFDC program the California Work Opportunity and Responsibility to Kids Program (CalWORKs). California Department of Finance budget worksheet. (December 2000). '4) Burchinal, M. (1999). Child care experiences and developmental outcomes. In S. Helburn (Ed.), The silent crisis in US. child care. Annals of the American Academy of Political and Social Science, 563, 73-97; Helburn, S. (Ed., 1995). Cost, quality, and child outcomes in child care centers: Technical report. Denver. CO: Department of Economics and Social Policy. University of Colorado; Fuller, B., Raudenbush, S., Wei. L.. and Holloway, S. (1993). Can government raise child care quality? The influence of family demand, poverty, and policy. Educational Evaluation and Policy Analysis, 15, 255-278. Holloway, S., Kagan. S.L.. et al. (in press). Assessing child-care quality with a telephone interview. Early Childhood Research. Caution is warranted in comparing California and Connecticut numbers. since participants in the two samples were about 6 versus 18 months into their respective state welfare programs. 6 Fuller. B.. Kagan. S. L.. ct a1. (2000). Remember the children: Mothers balance work and child care under welfare reform. (Technical supplement.) Berkeley: University of California and Yale University. \I Burchinal (1999). The principal components analysis. a statistical procedure for discovering how individual measures cluster together into composite indices. is available from the authors. 9 The wider Bay Area sample of FCCHs is sketched in section 1 and detailed in Holloway. Kagan et al. (in press). .— 0 Carroll. J. (2001). How to pay for child care? Local innovations help working families. Berkeley: University of California and Yale University (Policy brief). “ Fuller, 8.. Kagan. S.L.. et a1. (2001). Explaining family demand for early education: Household factors and neighborhood organizations. Berkeley: University of California (manuscript). ‘3 Fuller, Kagan. et a1. (2000). 30 U.C. BERKELEY LlB ARIES “mm...“ lllllllllllllllllllllll/ . C J. 1, Related GUP PrOJect reports on child care, early education, and working families. c”: L' 71‘3 7 Research Reports Fuller, Kagan, et al. (2000). Remember the Children: Mothers Balance Work and Child Care under Welfare Reform. Berkeley: University of California and Yale University. Holloway, Kagan, et al. (in press). Assessing child-care quality with a telephone interview. Early Childhood Research Quarterly ‘ Liang. Fuller, and Singer. (2000). Ethnic differences in child care selection: Influence of family structure, parental practices, and home language. Early Childhood Research Quarterly, 15, 357- 384. “ Fuller, Kagan, et al. (2001 ). Explaining family demand for early education: Household factors and neighborhood organizations. Berkeley: University of California (manuscript) Policy Briefs Carroll (2001). How to pay for child care? Local innovations help working families. Jacobson. (2000). Are child care options expanding? Jacobson, et al. (2001). Understanding child care demand and supply issues: New lessons from Los Angeles. To order PACE publications, please call 510-642-7223. Most are available on the Web at pace.berkeley.edu. Hardcopy research reports are $20,- policy briefs are $10. Acknowledgments A heartfelt thanks goes to center directors, family child-care homes, and individual caregivers who trusted us to visit and assess their ways of raising children. The Growing Up in Poverty Project is codirected with Sharon Lynn Kagan at Teachers College, Columbia University. Special thanks go to our Bay Area field coordinators, Gretchen Caspary, Christiane Gauthier, and Jim Mensing. Dora Wong and Norma Herrera completed much of the scoring and data entry tasks with care and good hu- mor. County officials and child-care leaders have been enormously open and supportive of con- fronting tough issues. The Spencer Foundation supported Sawako Suzuki's efforts on the project. Analytic and dissemination work for this paper was supported by the Packard Foundation and the MacArthur Foundation. Special thanks are due Marie Young and Laurie Garduque, respectively, for their unflagging support. The project would not be possible if not for the collaboration and encour- agement of Patty Siegel and Shelley Waters Boots at the California Child Care Resource and Referral Network. Fran Kipnis was with us from the beginning as well. Overall project funding has been generously provided by the Casey and Spencer foundations, the Miriam and Peter and Walter and Elise Haas funds, California Department of Social Services, Child Care Bureau of the US. Department of Health and Human Services, and US. Department of Education (OERI). Editing of the report was done by Bob Hass and graphic design by Joanne Klein. Thank you all. Bruce Fuller, Berkeley Policy Analysis for California Education PACE University of California, Berkeley and Stanford University 5655 Tolman Hall Berkeley, CA 94720-1670 Telephone: (510) 642—7225 ntto: ~oaceberl