Patterns of Resource Distribution in a Decentralized Urban Public School System Lynn W. Bachelor Decentralization in the Detroit Public Schools resulted in the establishment of administrative regions and the sharing of responsibility for resource allocation among regional and central administrators. This study examines the relationship between resource levels (measured by per pupil spending and pupil-teacher ratios) and demographic characteristics of schools in each region. Regression analysis revealed differences among regions, with some allocating more resources to schools in lower-income neighborhoods and others favoring middle-income areas. Variations were also found in patterns of distribution of federal and state compensatory funds. These differences, the study concludes, were the consequence of utilization of different decision rules and responsiveness by regional administrators to different population groups.

Lynn W. Bachelor, Department of Political Science, Wayne State University.

Studies of the distribution of urban public services have shown that neither race nor class nor political influence affects the quantity or quality of services such as parks, streets, schools, libraries, and police protection received by citizens in any systematic or intentional fashion (Levy et al., 1974; Lineberry, 1977). Inequalities in service levels, instead, appear to result from bureaucratic "decision rules," consisting of "professional norms', rules and regulations of superordinate bodies, loose perceptions of both needs and demands, and a search for economizing devices when perceived demands exceed perceived capacity" (Lineberry, 1977, pp. 153154). The use of multiple decision rules results in what Lineberry termed ' 'unpatterned inequalities": some rules favor middle-class areas and others favor low-income groups. According to Levy et al. (1974), decision rules vary among bureaucratic agencies; administrators in different divisions of the same agency may also use different rules in allocating resources. The present paper examines the distribution of resources in a decentralized urban school system in order to ascertain whether uniform rules of resource allocation are employed (as evidenced by uniform patterns of resource distribution). The relationship of socioeconomic variables to spending levels and class size in Detroit public schools was found to vary among the eight administrative regions into which the school district was divided, indicating that regional administrators used different rules in distributing funds to individual schools. The finding also suggests that patterns of resource distribution may be different when one set of adminisThe Urban Review

(~Agathon Press, Inc.

Vol. 16, No. 1, 1984 43

44

THE URBAN REVIEW

trators is making decisions for the entire district, an issue of particular relevance in Detroit in the context of a recent referendum by voters to recentralize the school administration. GENERAL PATTERNS OF EDUCATIONAL RESOURCE DISTRIBUTION Detroit's school system is of particular interest for a study of resource distribution because it was the subject of one of the earliest studies of intradistrict allocation of educational resources, Sexton's Education and Income (1961). Sexton examined both performance and resource indicators in relation to a rank ordering of schools by average family income in attendance areas and found that lower-income students were generally in larger classes and older buildings, received fewer services, and were more likely to be taught by substitute teachers (Sexton, 1961, pp. 33-34, 114, 119-120, 123-125). More recent analyses of educational resource allocation in Detroit and elsewhere, however, have not discovered such clear-cut patterns. Katzman (1971) found that, in Boston's public schools, there was no consistent pattern of bias in the distribution of resources controlled by school administrators (p. 132). In Oakland, Levy et al. (1974) found resources to be distributed in a U-shaped curve, with children in the lowest and highest income areas receiving the highest levels of resources (pp. 66-67). Mandel's analysis of Detroit elementary schools (1974) also found mixed distributional patterns. Discretionary spending per pupil (not including compensatory funds) increased with percentage white and socioeconomic status; compensatory spending per pupil decreased as socioeconomic status and percentage white increased; pupil-staff ratio increased with socioeconomic status and was highest in all white schools and lowest in integrated schools (Mandel, 1974, pp. 82, 86). Decentralization and Resource Distribution The Sexton and Mandel studies, however, preceded Detroit's highly controversial decentralization program. Proposed by a black state senator (Coleman Young, now mayor of the city) as a means of giving Detroit's black community more influence over educational policies, decentralization was transformed by central administrators into an instrument for preserving racial segregation (through the drawing of district boundaries) and increasing black representation in the school bureaucracy (by establishing new regional bureaucracies). To both blacks and whites, the program offered the expectation of influencing the distribution of resources through the new regional boards and regional bureaucracies. For this reason, it was hypothesized that distributional patterns (the relationship of school resource levels to demographic variables) would vary among the regions, as administrators responded to different constituencies and employed different decision rules.

DECENTRALIZATION AND RESOURCES

45

According to guidelines adopted by the Detroit Board of Education in October 1970, the school budget, a critical document in resource allocation, is to be prepared and adopted by the Central Board of Education, but requests of regions are to be taken into account. Following adoption of the general operating budget, each regional board then prepares a budget for its region, which must conform to its allocation from the Central Board. Allocation of funds within a region is described as a"discretionary responsibility of the Regional Board," limited by "standards mandated by law, these guidelines, and collective bargaining agreements"; regional boards are to identify educational priorities and fund educational programs on that basis (Detroit Board of Education, 1970, pp. 38-39). Regions are also to be responsible for developing and administering programs funded by categorical federal and state aid, in accord with the guidelines of these funding sources and the money assigned them by central administrators (Detroit Board of Education, 1970, p. 36). Interviews with school officials provided more detailed information on these procedures and substantiated the involvement of both school and regional officials in the preparation of the general operating budget. Schools submit request budgets to regional officials, who submit regional summaries to the central administration, where a total request budget is prepared. When revenue estimates become available, revisions are made by central office units, regions, and individual schools. Once the balanced budget has been adopted by the central board, allocations are made to regions and then, by regional officials, to individual schools. Regional officials also have some discretion in allocating funds from the major categorical compensatory aid programs, Title I of the Elementary and Secofidary Education Act of 1965 and Article 3 of the Michigan School Aid Act, within the limits imposed by state and federal eligibility guidelines. Title I eligibility is determined by a formula that uses census data and data on AFDC recipients to obtain a ''poverty index" for the district as a whole and for individual schools. Any school whose index is above the city average is eligible for Title I funds; another formula targets these funds to elementary schools by assigning more weight to elementary students in allocating funds. Article 3 provides funds for the development of reading and mathematics skills in grades K through 6; eligibility is based on the percentage of students who attained less than 40% of the objectives on a state assessment battery. Funds are allocated to the district (Detroit) on the basis of the number of eligible students, then distributed to regions. In both Title I and Article 3, regional coordinators distribute funds to individual schools after deducting administrative expenses and the cost of regional programs from the sum allocated to the region by the central Department of Federal, State, and Special Programs on the basis of the number of target students in the region. Interviews with regional administrators indicated that some used different formulas in distributing funds among elementary, middle, and high schools, and that others allowed exceptions to a strict "dollars × number of target students" formula in distributing funds. In order to determine the influence of regional officials on the distribution

46

THE URBAN REVIEW

of regular and compensatory funds, the present study analyzes the relationship of demographic characteristics to resource levels in elementary and middle schools in each region for 1977-1978. Variations in this relationship (e.g., higher resource levels in lower-income schools in some regions and lower levels in these schools in others) are considered indicative of the use of different decision rules by regional superintendents and coordinators and their responsiveness to different constituencies. Demographic characteristics were measured by school records on racial composition of the student body and the poverty index used in determining eligibility for Title I ESEA funds. (In 1977-1978, census data on poverty were weighted 65% and AFDC data 35% in computing this index.) The poverty index was supplemented by information on housing and distance to the Central Business District (CBD) for school attendance areas; these variables were reported by Jones et al. (1977, p. 154) to be reliable socioeconomic indicators for Detroit. Student-teacher ratios and levels of per pupil spending from general funds and state and federal federal compensatory programs served as indicators of resource levels in each school and constituted the dependent variables in regression analyses of allocational patterns in the district as a whole (248 schools) and in each region (approximately 30 schools per region). DISTRICTWlDE PATTERNS: WEAK RELATIONSHIPS Initial multiple correlation analysis for all Detroit elementary and middle schools indicated no relationship between spending levels and any of the demographic variables. Pupil-teacher ratios varied inversely with the poverty index (R = - .206) and housing age (R = - .286) and increased with distance from the CBD (R = - .300). That innercity, schools had lower pupil-teacher ratios but did not have consistently higher spending levels suggests the combined effect of declining enrollments and less experienced (and therefore lower paid) teachers; in the absence of data on average teacher experience levels for individual schools, however, concentration of less experienced teachers in inner-city schools cannot be demonstrated. Multiple regression analysis, as expected from the low correlation coefficients, revealed that the socioeconomic variables explained relatively little of the variance in per pupil spending or pupil-teacher ratios. For per pupil spending, R 2 = .038, and none of the demographic variables had significant F values; for pupil-teacher ratio, R z = . 124, and only the poverty index had a significant F value. REGIONAL PATTERNS: COMPENSATION A N D DISCRIMINATION Regression analysis of socioeconomic variables and resource indicators revealed differences among regions in the relationship of demographic variables and resource levels. The absence of a clear-cut relationship at the districtwide level was apparently a consequence of "compensatory" patterns in some regions (more resources in lower-income areas), "dis-

DECENTRALIZATION AND RESOURCES

47

criminatory" patterns in others (fewer resources in lower-income areas), and mixed relationships in a third group. In all but one region, demographic variables explained a much larger percentage of the variance in resource levels than they did for the district as a whole; although few of the beta values were statistically significant, they are indicative of variations in the strength and direction of relationships with the resource measures. The regions also differed from each other in their demographic composition, reflecting the racial and socioeconomic differences among Detroit neighborhoods. Although they are only administrative units, the regions exhibited significant variations in mean values of the poverty, housing age, and race variables (see Table 1). These variations were associated with different resource allocation patterns, suggesting that'decision makers were influenced by constituency pressures. Compensatory Patterns

In two regions, allocational decisions favored schools with large proportions of disadvantaged students (see Table 2). In Region C, which had the highest poverty rate and the oldest housing of the eight regions, schools with higher proportions of low-income students had significantly lower pupil-teacher ratios and higher spending levels. There was also evidence of a compensatory distributional pattern in Region D. The indirect indicators of socioeconomic status, distance, and housing age, as well as the poverty index, were strongly related to spending levels and pupil-teacher ratios in this region. Both of these regions are old, inner-city areas with high poverty rates, characterized by declining population and school enrollments. The number of teachers in such schools declines more slowly, because the enrollment in a particular grade must decline by the equivalent of one class before a reduction in teaching personnel can be made; even then, the reduction is not immediate because contractual procedures governing involuntary transfers TABLE 1. Characteristics of Regions (Mean Values of Socioeconomic Variables) Region A B C D E F G H

Poverty 15.24% 21.38 31.79 26.61 15.67 15.78 12.03 16.57 F = 33.465 Prob. = 0.0000

Housing Age 40.45 56.91 62.17 58.20 41.36 39.36 31.83 34.97 F = 63.715 Prob. = 0.0000

Proportion Black Students .72 .59 .90 .96 .69 .98 .77 .82 F = 19.418 Prob. = 0.0000

.396*

.281 .346

.440 .331

-.250 -.251

.468

-.213

.117

R2

-.167

.541

Distance % Black students Housing age Poverty % Black educ. personnel ,489

.145

,241 -.819"**

.204

-.088

Pupils/ Teacher

C

.453

-.497

.240 .588**

.340

.290

Spending

.372

-.371

-.689 -.398

1.406

.177

Pupils/ Teacher

,608

-.191

-.215 .365

-,580

.129

Spending

.220

-,193

.0002 .199

-.166

-,307

Pupils/ Teacher

F

E

Spending

D

Pupils/ Teacher

Independent Variables

"Discriminatory" Regions

"Compensatory" Regions

.309

.354

-.017 -,577

-.087

-.058

Spending

TABLE 2. Beta Values for Regressions for PupiisfI'eacher and Spending Levels, by Regions

R2 .269 aWith interaction term. blnteraction variable. *Significant at .05 level. **Significantat .01 level. ***Significant at .O01 level.

.385*

.363

.257

- .231 .138

- .354 - .317

.328

Spending

-.298

- .786**

Distance % Black students Housing age Poverty % Black educ. personnel

G

-.391

Pupils/ Teacher

Independent Variables

T A B L E 2. (continued)

.161

-.458

.351 --.729

.481

- .444

Pupils/ Teacher

A

.241

- .366

- .431 -.056

-.308

- .822*

Spending

.116

.265

- .056 - .476

.244

- . 108

Pupils/ Teacher

B

.135

.189

- .734 .126

-.469

- .740

Spending

" M i x e d " Regions

.509

.045

- 1.214"** .189

1.219"**

.234

Pupils/ Teacher

H

.233

,294

.370 --.386

--.607

.066

Spending

Ha

- 2 . 1 1 3 b* .520

-068.

.121" .236*

2.138*

.299*

Pupils/ Teacher

N

0

I'M

z o

Z

,=4

i

O

50

THE URBAN REVIEW

must be followed (teachers must be given one week's notice, seniority must be used to determine transfers, and teachers must be given a choice of schools). Because these involuntary transfers from schools with declining enrollments involve teachers with the least seniority, expenditure reductions are minimized (teacher salaries are the main component of these expenditures, and less experienced teachers have lower salaries). Lower student-teacher ratios and higher spending levels per pupil in schools with higher proportions of low-income students may simply be the result of declining enrollments in such schools. If this were the case, however, the same strong relationship between resources and poverty would exist in all regions and in the district as a whole. That it did not suggests that regional superintendents in these two impoverished areas made an effort to put additional resources into schools in the most impoverished neighborhoods of their regions, boosting resources above those levels that would result only from enrollment decreases.

Discriminatory Patterns "Discriminatory" distributional patterns (favoring schools with lower proportions of low-income or black students) were found in two regions, which were dissimilar in socioeconomic attributes (see Table 2). Region E had a relatively low proportion of black students, while Region F had the highest of any region; both had relatively low proportions of low-income students and relatively new housing. In Region E, racial composition was the most significant determinant of both spending levels and pupil-teacher ratios. Higher pupil-teacher ratios and lower spending levels in schools with higher percentages of black students are suggestive of discrimination, especially in the presence of weak compensatory relationships with the poverty indicator. This region, once predominantly white, has been experiencing racial transition. The privacy of personnel records prevented documenting whether experienced white teachers have been transferring out of predominantly black schools, but statements of officials suggest this has been happening. In addition, racial transition has been accompanied by enrollment increases. The combined effect of these trends would be a reduction in per pupil spending as senior teachers were replaced by less experienced ones, and higher pupilteacher ratios resulting from increased enrollments without personnel increases. There was fairly strong evidence of bias against schools with high proportions of low-income students in Region F. Per pupil spending was lower in schools with higher poverty rates, and pupil-teacher ratios were higher in schools nearer the CBD. This area has experienced complete racial transition (98% of its students are black) and is now undergoing the socioeconomic transition that has often followed in Detroit. While this pattern may be due in part to enrollment increases in lower-income areas, it may also be a response to pressure from middle-class parents to preserve the quality of schools in their neighborhoods. One administrator identified an

DECENTRALIZATIONAND RESOURCES

51

east-west street as dividing the region into a low-income and middle-income area. That the middle-income area, located farther from the CBD, had lower pupil-teacher ratios, was evident in the strong negative relationship between this variable and the distance measure. The low-income area is experiencing population and enrollment growth, and administrators have not put additional personnel into these schools, resulting in lower per pupil spending levels. Unpatterned Inequalities

In two of the regions where "mixed" patterns existed, relationships with both resource indicators were much weaker than in the' 'compensatory" or "discriminatory" regions (Table 2). In Region A, both discriminatory and compensatory tendencies were evident in the regressions for both resource variables. This region has relatively few disadvantaged students and relatively new housing, but it is located in an area of declining population. Apparently administrators made some effort to help lower-income schools, while population movements contributed to higher spending levels and lower pupil-teacher ratios in better-off areas. Region B, in contrast, had a relatively high percentage of low-income students, relatively old housing, and the lowest proportion of black students in the eight regions; it includes Detroit's predominantly Latino neighborhoods. Although relationships with the resource indicators were quite weak, they suggested a tendency to favor schools with high proportions of low-income students and low proportions of black students, perhaps reflecting an effort to allocate additional resources to schools in low-income Latino areas. Slightly stronger mixed relationships were found in Regions G and H. In Region G, which had the newest housing and smallest proportion of lowincome students of any region, pupil-teacher ratios were negatively related to both the proportion of disadvantaged students and the distance variable (which were themselves negatively correlated). Examination of scatterplots indicated some curvilinearity in the relationship of poverty and pupilteacher ratios, suggesting that both declining enrollments (in schools with higher proportions of low-income children) and administrative discretion (in schools with few low-income students) may have affected these relationships. A more confusing mixed pattern was evident in Region H. The regression for per pupil spending clearly indicated a discriminatory pattern. Both the proportion of black students and the proportion of low-income students were negatively related to spending levels. The findings for pupil-teacher ratios, however, were problematic: a strong negative relationship with housing age and a strong positive relationship with percentage of black students. Scatterplots of these relationships indicated a strong positive relationship between housing age and pupils per teacher, and a slight curvilinear relationship between percentage of black students and pupils per teacher (lower ratios in those schools with the highest and lowest percentages of black students). The strength of the relationship between housing

52

THE URBAN REVIEW

age and racial composition suggested the operation of an interaction effect in the regression. Inclusion of this interaction term reduced the significance of both independent variables in the regression, although it was not itself significant. The regression coefficients indicate a fairly strong positive relationship between the proportion of black students and pupils per teacher, but a slight negative relationship when both old housing and a high proportion of blacks characterize a school (interaction term). These results confirm the hypothesis of a curvilinear relationship with pupils per teacher and reflect declining enrollments in schools with the highest proportions of blacks, in older neighborhoods. Population growth areas, which lie in the median range on housing age and have relatively large proportions of black students, seemed to have the highest pupil-teacher ratios, while those schools with the fewest black students also had low ratios, suggesting a favored status with administrators.

DISTRIBUTION OF COMPENSATORY FUNDS In order to determine whether regional administrators influenced the distribution of compensatory as well as regular funds, mean per pupil Title I and Article 3 allocations for each region were computed, by dividing each school's allocation by its number of Title I or Article 3 target students and averaging these school-level figures. Because different Title I allocation formulas are used for elementary and middle schools,Z an effort was made to exclude nonelementary schools from this analysis. These figures suggested considerable interregional variations, particularly for Title I spending levels (see Table 3). Although the central office of Federal, State, and Special Programs allocates Title I money to regions on a uniform per pupil figure for elementary schools, regional Title I coordinators evidently differed in how they allocated these funds among individual schools and central and regional programs, with some putting more money into centrally and regionally operated programs and others putting more into programs developed by individual schools. (These figures should not be interpreted as TABLE 3. Regional Variations in Compensatory Spending Levels Re~ion A B C D E F G H

Mean Title I Spending per Pupil $659.37 709.04 NA 420.95 674.10 668.36 794.24 NA F = 14.919 Prob. = 0.000

Mean Article 3 Spendingper Pupil $226.03 228.04 226.72 276.59 209.66 213.88 207.04 226.52 F = 3.859 Prob. = 0.000

DECENTRALIZATION AND RESOURCES

53

meaning that a Title I student in one region gets any fewer Title I resources, since such a student can participate in a regional, central, or individual school program.) Interviews with regional Title I coordinators illuminated some of the influences on allocational decisions. According to one administrator, documentation on a particular program could result in higher allocations for some schools, presumably by demonstrating the merit of that school's funding request; this coordinator consistently allocated more money to elementary schools and less to middle and high schools than was generated by the "target students × dollar amount" formula. In another region, nearly half of the Title I allocation was put into regional programs, and a formula of 6-3-1 was used to allocate the remaining funds to elementary, middle, and lligh schools, respectively. A third coordinator, although unable to provide school-by-school figures on allocations, reported that an effort was made to help schools with declining enrollments through "special needs" money; weights of 7, 3, and 1 were used throughout this region, with a 6-4-1 formula in one area to give more money to a junior high school (which, because it did not include any 6th-graders, would not benefit from the higher per pupil amount for elementary students). As in Title I, regional Article 3 coordinators differ in the proportions of money allocated tO regional programs and individual schools. The central office of Federal, State, and Special Programs reported that two regions used different procedures in distributing Article 3 funds: one region allocated"compensatory educational personnelresources to each school based on an enrollment factor, and remaining funds [e.g., for s u p p l i e s ] . . , on a per-target-pupil basis" so that the dollars per pupil were different in each school; another region deducted the cost of "Precision Teachers [teachers specially trained to handle reading and math deficiencies] assigned to most schools" and then distributed the balance on a per-target-pupil basis (Dunn, 1978). D E M O G R A P H Y VERSUS A D M I N I S T R A T I V E DISCRETION

These differences between regional and citywide distributional patterns, and among regions indicate that the involvement of regional administrators in budget preparation and allocation of funds had an impact on the distribution of resources in the Detroit Public Schools. However, the regions, as indicated in Table 1, may be socioeconomic as well as administrative units. Regional differences may simply be the consequence of socioeconomic differences. To gain some insight into the relative impact of region and socioeconomic variables as influences on resource levels, " r e g i o n " was entered as a dummy variable in districtwide multiple regressions for student-teacher ratio and per pupil regular spending. Addition of the region variables slightly increased the percentage of variance explained by each of the regressions, but considerable multicollinearity was evident in the relatively small and generally insignificant

54

THE URBAN REVIEW

betas for these variables (see Table 4). The influence of region seemed somewhat greater in the expenditure equation than in that for pupil-teacher ratios. This suggests that administrators have more control over the allocation of funds than over pupil-teacher ratios, which are largely determined by enrollments and the teachers union contract. The " r e g i o n " variables in the spending equation were more significant than the socioeconomic ones, indicating that regional differences were more important influences on spending levels than were demographic variables. At the regional level, however, administrators responded to socioeconomic characteristics. Regional administrators in the lowest income regions favored schools with the highest proportions of disadvantaged students; those in areas with the fewest disadvantaged students favored schools with the lowest poverty levels. In each case, the administrator's behavior can be explained as a response to the community majority or to political pressures from a dominant population group. In the case of Title I and Article 3 funds, which must be targeted to the educationally and economically disadvantaged, variations are more the consequence of the use of different decision rules related to the division of funds among regional, central, and individual school programs, or among elementary, middle, and high schools.

CONCLUSIONS The differences in patterns of resource distribution among regions in the Detroit Public Schools appear to be the product of both different decision rules and responsiveness to different constituencies. Patterns in the allocation of regular funds appeared to be the product of responsiveness to majority population groups, while differences in the distribution of compensatory funds appeared to be the result of different decision rules. Clearly, then, decentralization has had an important effect on resource distribution. Regional school boards and superintendents have tended to respond to regional majority population groups, allowing geographically concentrated groups which are citywide minorities to exert some influence over the distribution of resources. Regional Title I and Article 3 coordinators can also justify variations from central funding formulas by reference to unique needs of students or schools in their region. In this way, administrative decentralization has promoted some of the same objectives as district-based city councils, by broadening the range of interests represented in policymaking. It must be acknowledged, however, that resource allocation decisions, despite their significance, are only part of the policymaking process in an urban school system. Equally important are two additional concerns articulated by many community-control advocates: teaching personnel and curriculum. Decision making in these areas has been closely guarded by central administrators and union officials; one would expect to find much less regional variation than in patterns of resource distribution. Another concern of community-control advocates was improvement of

DECENTRALIZATION AND RESOURCES

55

TABLE 4. Citywide Regressions with Dummy Variables Variable Pupil/Teacher Ratio Poverty Housing age Distance % Black students % Black educational personnel Dummy 1 Dummy 2 Dummy 3 Dummy 4 Dummy 5 Dummy 6 Dummy 7

b

Beta

F

Si~.

- . 112 - .077 - .535 -1.004

- .20105 1.20619 -0.32477 -.04636

2.475 0.754 1.591 0.142

.01 N.S. N.S. N.S.

7.829 -1.319 - 1.346 .0493 5.353 .0725 1.090 -.773

.19101 -.08571 .10095 .03386 .38532 .04617 .06794 -.04479

3.103 0.782 0.837 0.083 6.582 0.177 0.445 0.211

.001 N.S. N.S. N.S. .1301 N.S. N.S. N.S.

R 2 = . 19030 General Per Pupil Spending Poverty Housing age Distance % Black students % Black educational personnel Dummy I Dummy 2 Dummy 3 Dummy 4 Dummy 5 Dummy 6 Dummy 7

Df = 12;176

.881 .641 1.607 - 145.693

.06056 .06577 •.03737 -.25772

0.201 0.069 0.019 3.938

N.S. N.S. N.S. .001

50.947 -43.134 - 11.624 -91.883 -74.061 -87.056 - 106.415 -.42.128

.04762 - . 10739 -.32088 -.24166 -.20425 -.21227 -.25412 -.09357

.0173 1.101 7.587 3.796 1.658 3.358 5.584 0.826

N.S. N.S. .001 .001 N.S. .001 .001 N.S.

R 2 = .09702

Df = 12;176

the q u a l i t y o f education in inner-city schools. W i t h o u t b e c o m i n g involved in the difficult issue o f m e a s u r i n g educational quality, it should be pointed out that the c o n n e c t i o n b e t w e e n resource levels and educational quality is t e n u o u s at best. That l o w - i n c o m e schools have been favored in the distribution o f financial resources, then, cannot be taken as evidence that the quality o f e d u c a t i o n was higher in these schools. N e v e r t h e l e s s , the finding that decentralization allowed for greater r e s p o n s i v e n e s s to c o m m u n i t y majorities in the allocation o f funds is not i n s i g n i f i c a n t , in the light o f a recent vote to recentralize the Detroit Public S c h o o l S y s t e m . The c a m p a i g n against decentralization focused on its costs a n d the l a c k o f p o l i c y authority granted to regional boards. W h i l e the first p o i n t is i n d i s p u t a b l e , it appears unlikely that substantial savings will be a c h i e v e d from recentralization because regional bureaucracies will be

56

THE URBAN REVIEW

reabsorbed. The second point, about lack of policy authority, seems, on the basis of the findings reported here, to have been exaggerated. Recentralization can be expected to result in more uniform patterns of resource allocation. Who will gain and who will lose under these new rules remains to be seen. NOTES

2.

The Jones data, which were compiled for census tracts, were reorganized and recomputed for school attendance areas with the aid of tables (matching census tracts with school attendance areas) provided by Dr. John Lindsey of the Office of Research and Evaluation in the Detroit Public Schools. The central office allocates Title I money according to a "7-2-1" formula, in which elementary school target students are assigned a weight of 7, middle school students a weight of 2, and high school students a weight of 1. In 1977-1978, this formula produced $855.53 per elementary student, $244.54 per middle school student, and $122.57 per high school student. These figures are used to calculate a "money generated" figure for each school by multiplying the per pupil amount by the number of target students in each category at each school. "Money generated" figures are then summed for each region, and a lump sum is allocated to the regional Title I administrator. Administrators deduct administrative expenses and the cost of participation in central and regional Title I programs, then distribute the remaining funds to individual schools. Data on these distributions were available for only 6 of the 8 regions.

REFERENCES Detroit Board of Education. Guidelines for Regional and Central Boards of Education of the School District of the City of Detroit. October 26, 1970. Detroit Board of Education. Dunn, S. (Department of Federal, State, and Special Programs, Detroit Public Schools). Letter to the author, December 20, 1978. Jones, B. D., Greenberg, S., Drew, J., and Kaufman, C. Bureaucratic response to citizeninitiated contacts: environmental enforcement in Detroit. American Political Science Review, 1977, 71, 148-165. Katzman, M. T. The Political Economy of Urban Schools. Cambridge: Harvard University Press, 1971. Levy, F. S., Meltsner, A. J., and Wildavsky, A. Urban Outcomes. Berkeley: University of California Press, 1974. Lineberry, R. L. Equality and Public Policy. Beverly Hills, Calif.: Sage Publications, 1977. Mandel, A. S. Resource allocation inside school districts. Ph.D. dissertation, University of Michigan, 1974. Sexton, P. C. Education andlncome. New York: Viking Press, 1961.