ࡱ> qsnop@ jbjbqq "Lzl&&&&&\&hZ Z Z Z Z Z Z Z hhhhhhh,tj lhZ Z Z Z Z h, Z Z Z , , , Z Z Z h, dZ h, j, _v 5&& L+_4Qhh3,>m, >m_,  THE BEST SCHOOL DISTRICTS IN TEXAS FOR LATINO STUDENTS 1999-2002 Kenneth J. Meier Robert D. Wrinkle Daniel Hawes and Nick Theobald A REPORT OF THE TEXAS EDUCATIONAL EXCELLENCE PROJECT NUMBER 22 OCTOBER 10, 2003 For further information, contact: Nick Theobald at theobald@polisci.tamu.edu http://teep.tamu.edu Or, in South Texas Robert D. Wrinkle, Department of Political Science, University of Texas Pan American, 956-381-3341; rdwe116@panam1.panam.edu The Texas Educational Excellence Project (TEEP) is a joint program of the George Bush School of Public Service and the Department of Political Science at Texas A&M University. The project also has research associates at the University of Texas Pan American and Oakland University. TEEP seeks to apply scholarly research to educational policy issues in order to make recommendations for greater quality and equity in Texas school systems. The Best School Districts in Texas for Latino Students 1999-2002 The education of minority students is of primary concern for education leaders and policy-makers in Texas. In recent years, minority students have made impressive gains on the statewide TAAS exam. However, Latino students continue to lag behind Anglo students in TAAS scores, Texass primary measurement of basic skills. Latino students, however, have made great strides in closing this gap. In 1996, 54.2% of Latino test-takers passed the TAAS, compared to 79.8% for Anglo students, a gap of 25.6 percentage points. By 2002, Latino students cut this gap in half to 12.8 percentage points, scoring an average of 79.7% compared to an average of 92.5% for Anglos in that year. Indeed, this is evidence of significant progress. However, these statewide gains are not evenly distributed across all districts. Some school districts have made even more impressive gains while others have fallen behind. The Texas Educational Excellence Project believes that by identifying those districts that do a better job in educating Latino students, Latino TAAS performance can be further improved. The programs and policies used by the exemplary districts may then be used as a standard by which other districts can measure and improve their own performance. The Bangs Independent School District provides one such example. Taking resources and environmental factors into account, the predicted three-year average pass rate for Latino students at Bangs was 77.48%. The 1999-2002 Bangs Latino average pass rate was, in fact, 91.5%, over 14 percent better than expected. In 2002, 92.9% of Latino students in Bangs passed the TAAS. This impressive pass rate for Latino test-takers helps the district achieve the highest score in our ranking system. This is the second consecutive year in which Bangs ISD has achieved the top rank. Bangs superintendent James Hartman attributes the districts success to an emphasis on involving all students regardless of ethnicity. Bangs ISD makes special efforts to provide opportunities for student involvement in scholastic and extracurricular activities. Hartman believes that this involvement leads to a sense of belonging among the students, which in turn contributes to greater success. Another exemplary school district is Grand Saline. This school district ranked second overall, and first place for the 2002 TAAS test under the TEEP ranking system. Gerald Gilbert, Grand Salines superintendent, attributes their success to their emphasis on early intervention programs. Non-English speaking children are engaged in academic programs at an early age where phonics is emphasized. However, Gilbert considers the greatest factor to their success be parental involvement in the students schooling as well as energetic teachers with a desire to teach. Both Bangs and Grand Saline are relatively small school districts, and their approaches might not readily transfer to larger districts. However, some large districts, such as Galena Park, also have done an exemplary job at educating Latino students. In 2002, Galena Park ISD had a Latino student pass rate of 88%. This is particularly impressive since over 65% of the students in this district live in poverty. The Texas Educational Excellence Project uses an analytical technique called multiple regression to identify which school district do a better job at educating Latino students. This technique allows important variables be considered, rather than simply comparing TAAS rates, which would ignore factors that influence performance. School districts often have little or no control over such external factors. By utilizing multiple regression, we can assess the impact of particular policy and resource related variables while holding other variables constant. Using this method, TEEP is able to rate a school districts overall performance in educating Latino students while controlling for the level of institutional resources. This provides a more valid basis of comparison of performance between individual school districts. The model used in this analysis is based on what the literature defines as an educational production function. A large literature has been developed which designates various education production functions to evaluate the outputs of schools to their inputs (Burtless 1996; Smith 1995; Hanushek, 1986; 1989; 1996). In this function, performance (here identified as Latino pass rates on the TAAS) is a function of various inputs into the educational process. These inputs include the districts level of operating expenditures, percent of low-income students, the poverty level of the district, level of education of Latinos in the district, and various educational policies of the district. The prediction of how well the district should perform in educating Latino students is a result of the estimation of the established production function. Thus, with the results of the estimation, we can compare how well districts actually perform to how well the model predicts they will perform given a certain level of resources. This difference of actual to predicted is the measure of how well the districts are doing in educating Latino students. In other words, those districts that actually perform better than predicted, are those districts that are doing a superior job of educating Latino students. The 1999-2002 Education Production Function The dependent variable in our production function is the school districts TAAS pass rate for Latino students. All school districts in Texas are required to annually administer the TAAS exam to students in a variety of grades. The district average for all grades is our dependent variable. Obviously, it would be incorrect to claim that this variable adequately captures the entire range of learning for Latino students. Indeed, we make no claims that this is an overall measure of Latino student learning. However, it is a measure of how well students do in acquiring basic skills. Thus, by rating school districts on this measure, we have a measure of how well the district does in teaching basic skills to Latino students. The independent variables in our analysis fall into four types: school district policies, environmental constraints, teacher quality, and financial resources. School district policies include class size, student attendance (percent attending on an average day), and the percent of students enrolled in gifted classes. Performance should be negatively related to class size and positively related to the two other policy measures. Environmental constraints are factors that hinder student performance. While school districts cannot adjust these factors, it is important to statistically control for them when assessing student performance. The measures of environmental constraint are the percentage of Latino families that live in poverty in that district and the percent of poor students (those who are eligible for free school lunches). Additionally, the educational level of Latinos within the district is measured using the percentage of Latinos in the district over age 25 with at least a high school education. This variable should be positively related to student performance while the poverty variables should be negatively related to student pass rates. Teacher qualification is measured in two ways: the percent of teachers within a district with only a temporary teachers certificate in a subject specialty (as opposed to a permanent certificate), and the average number of years of teaching experience. We expect that teacher experience should contribute to student performance, while the percent of non-certified teachers should negatively affect Latino pass rates. Among the most important factors are financial resources of the school district. However, the relationship between educational expenditures and student performance is controversial. Hanushek, in a variety of works (1986; 1989; 1996) finds no consistent relationship between money and student performance. For some time this finding has been the conventional wisdom for educational policy researchers. Lately, however, a number of researchers have qualified Hanusheks position. For example, in recent longitudinal studies, Murray (1995), Evans, Murray and Schwab (1997) and Murray, Evans and Schwab (1995) reported that districts that increased expenditures had improved student performance. A 1999 study by Bohte found that expenditures were correlated with higher test scores in Texas, even when controlling for the previous years test scores. In our analysis, we consider institutional resources and expenditures an important variable in our model. Financial resources are measured in three ways: instructional funds per student, average teacher salary, and the percent of funds received from the state. These measures characterize the total financial resources allocated to education, the districts ability to attract qualified teachers in a competitive marketplace, and the states efforts to compensate for the unequal distribution of local financial resources. All of these measures should be positively related to student performance. Texas school districts are diverse in both size and homogeneity. In order to use a set of organizations relatively similar in the tasks they perform, our analysis is limited to school districts with at least 1000 and at least 10 percent Latino students. The data analysis is a pooled time series with data from 1999 to 2002. Serial correlation, resulting from any trends in the variables over time, needs to be controlled for in any pooled time series analysis. A series of dummy variables are used to control of serial correlation. Table 1 shows the basic production function equation. Nine of the 11 variables are statistically significant. These include two of the environmental constraints, both teacher qualifications, two of the school district policies, and all three of the financial resources. Several variables are powerful predictors of Latino pass rates. Student attendance positively and significantly influences Latino student pass rates. The percentage of Latinos over age 25 with at least a high-school diploma is also a positive and significant predictor of Latino performance. Both teacher quality variables are statistically significant variable and in the anticipated direction. The coefficients for these variables indicate the amount of change in the dependent variable, Latino pass rates, that is related to a one-unit change in the independent variable. Thus, a one percent increase in enrollment in gifted classes produces a .19 percent increase in Latino TAAS pass rates. It should be noted, however, that schools have little or no control over these variables, particularly the environmental constraints. As such, it is difficult for schools to substantially improve Latino pass rates by simply adjusting the levels of these variables. However, some districts seem to better utilize the resources available to them. Furthermore, we can identify those districts by comparing the expected pass rates given the resources with the actual pass rates. This then allows us to compare school districts as to how well they perform relative to expectations. La Marque ISD, for example, was predicted by the model to have an average Latino pass rate of 71.3 for the period of 1999-2002. Their actual average pass rate was 83.5%; meaning 12.2% more Latino students passed the TAAS than expected. This significant achievement advances La Marque ISD from 19th place last year to fourth place for the 1999-2002 average. This improvement is, indeed, worth noting. Using this method, the top forty districts are listed in Table 2. The first column provides the numerical score on which the districts are ranked. The second column is the average pass rate for Latino students from 1999 to 2002. The last column is the residual score for the 2002 TAAS exam only. Bangs ISD performed 14.02 points better than expected, placing it in the top rank, followed closely by Grand Saline (+13.43) and Angleton (+13.41). The best 25 school districts for Latino students in 2002 only are listed in Table 3. Grand Saline ISD is ranked number one followed by La Joya and Mount Vernon. La Joyas 2002 score is particularly impressive, moving from a 1999-2002 average of 6.71 to 12.07 for 2002. La Joya ISD has made significant gains in the past year, moving from 21st place to 2nd place in one year. The gains in 2002 are likely the result of policies adopted earlier; thus, these are the districts that are likely to be rated highly in future studies. Large districts are distinct from smaller districts in that they face different challenges and often cannot change as rapidly as smaller district because more students are involved. Table 4 lists the ten best large districts (15,000 students or more) for Latino students. Galena Park holds is ranked the number one for the second consecutive year with a score of 9.61, followed by Ysleta (+8.69) and Aldine (+8.07). The Appendix alphabetically lists all the districts examined in this study, along with their score. Any person interested in a specific school district can examine the Appendix to locate that district and identify their score and rank. Conclusion This study has identified those school districts in Texas that performed better than expected on the TAAS pass rate for Latino students. These districts can serve as role models for other districts in Texas. The districts have a wide variety of programs for early diagnosis, student motivation, and parental involvement. Not all of the districts use the same approach, indicating that success can be attained in a variety of ways. If effective programs and performances from these districts are identified, then other districts can adopt them, which will result in an overall benefit to Latino students. Although this study only examines exemplary districts, that should not detract from the relatively low over-all TAAS pass rate for Latino students in Texas. In order to close the test gap between Latino and Anglo students, additional improvement is needed in these districts as well as other districts. Significant progress has been made in the last few years; yet, there is a great need for further improvement. Improving educational opportunities for all Texas children requires a long-term commitment to education. Improvement will require openness to innovation, as well as an emphasis on meaningful evaluation. References Bothe, John, 1999. "Class Size, Teacher Salaries and Student Performance." College Station, TX: Texas Educational Excellence Project. Burtless, Gary. 1996. Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success. Washington, D.C.: Brookings Institution. Culp, Cindy V. 2003. Waco Trustees Grade Promotion Policy Will Increase Number of Students Retained? Waco Tribune. http://www.wacotrib.com/news/newsfd/auto/feed/news/2003/04/10/1049951906.00353.1168.7802.html Hanushek, Eric A. 1986. "The Economics of Schooling: Production and Efficiency in Public Schools." Journal of Economic Literature 24:1141-77. Hanushek, Eric A. 1989. "The Impact of Differential Expenditures on School Performance." Educational Researcher 23 (4): 45-65. Hanushek, Eric A. 1996. "School Resources and Student Performance." In Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success, Gary Burtless, ed. Washington, D.C.: Brookings Institution. Hedges, Larry V. and Rob Greenwald. 1996. "Have Times Changed? The Relation between School Resources and Student Performance." In Does Money Matter? The Effect of School Resources on Student Achievement and Adult Success, ed. Gary Burtless. Washington: Brookings. Murray, Sheila E. 1995. "Two Essays on the Distribution of Education Resources and Outcomes." PhD. diss. Department of Economics, University of Maryland. Murray, Sheila E., William N. Evans and Robert M. Schwab. 1995. "Money Matters After All: Evidence From Panel Data on the Effects of School Resources." University of Kentucky and University of Maryland working paper: The Martin School. Smith, Kevin B. 1995. "Policy, Markets, and Bureaucracy: Reexamining School Choice." Journal of Politics 56 (May), 475-491. Table 1. Regression Results Latino TAAS Pass RatePercent Low Income-0.058(4.11)**Percent Gifted0.194(3.34)**Attendance2.963(10.34)**Average Teacher Salary K0.283(2.13)*Class Size0.293(1.32)Non-Certified Teachers-0.295(5.31)**Teacher Experience0.384(3.07)**State Aid0.033(2.90)**Instructional Expenditures0.003(3.00)**High School Education7.892(2.97)**% Poverty Background-3.863(1.80)y00-0.674(1.05)y011.888(2.79)**y025.131(7.11)**Constant-265.193(9.59)**Observations1338R-squared0.36 Absolute value of t statistics in parentheses significant at 5%; ** significant at 1% Table 2. Top 40 Districts in Texas RankDistrictScoreAverage TAAS Rate2002 Score 1Bangs14.0291.5010.202Grand Saline13.4388.0714.093Angleton13.4193.4511.844La Marque12.2083.509.005Mount Vernon12.1990.1811.876Brazosport11.7891.4010.087Del Valle11.7778.5711.878Los Fresnos Cons11.7489.577.789Monahans-Wickett-Pyote11.5290.3210.9610Valley View11.3986.8010.8311Burnet Cons10.8685.326.3212Alvin10.7383.7011.5313Hidalgo10.3185.0510.4814Columbia-Brazoria10.1688.1011.7415Ferris9.9984.409.0716Coleman9.6286.026.4917Galena Park9.6181.979.9918Bishop Cons9.5787.205.7019Calhoun County9.4185.787.3520San Benito Cons9.3582.588.6521Point Isabel9.1283.505.1822Ballinger8.7588.036.2623Ysleta8.6983.435.2224Merkel8.5188.258.1125Hereford8.4282.788.3226Willis8.2080.4310.6127Aldine8.0783.436.6328Pittsburg8.0281.620.5629Alice7.9574.8210.1430Sweeny7.8988.986.1931Plainview7.8780.656.6432Orange Grove7.8485.0010.1233Frenship7.7486.183.9234Denver City7.5687.256.1935Tuloso-Midway7.5383.203.7736Eagle Pass7.5378.505.1237El Campo7.5385.475.6238Galveston7.3576.207.7139Kaufman7.0881.072.6440Dumas6.9480.558.33 Table 3. Top 25 for 2002 RankDistrictScoreAverage TAAS Rate2002 Score 1Grand Saline13.4388.0714.092La Joya6.7173.9512.073Mount Vernon12.1990.1811.874Del Valle11.7778.5711.875Angleton13.4193.4511.846Columbia-Brazoria10.1688.1011.747Alvin10.7383.7011.538Groesbeck6.7781.0511.059Monahans-Wickett-Pyote11.5290.3210.9610Valley View11.3986.8010.8311Willis8.2080.4310.6112Hidalgo10.3185.0510.4813Bangs14.0291.5010.2014Alice7.9574.8210.1415Orange Grove7.8485.0010.1216Brazosport11.7891.4010.0817Galena Park9.6181.979.9918Presidio2.9265.759.9819McKinney0.7574.359.4720Bay City6.1777.989.3321Cuero1.3379.689.3222Ferris9.9984.409.0723La Marque12.2083.509.0024Childress3.6181.228.9525San Benito Cons9.3582.588.65 Table 4. Top 10 Large Districts (15,000 + Students) RankDistrictScoreAverage TAAS Rate2002 Score 1Galena Park9.6181.979.992Ysleta8.6983.435.223Aldine8.0783.436.634La Joya6.7173.9512.075Goose Creek Cons5.6780.405.136United4.6273.954.797McAllen4.5580.553.038Waco4.5176.077.679Harlingen Cons4.3882.574.1210Pharr-San Juan-Alamo3.3978.472.82 Appendix. Scores for All Scools RankDistrictScoreAverage TAAS Rate2002 Score 113Abilene2.4679.823.63284Alamo Heights-6.2181.38-6.6127Aldine8.0783.436.6329Alice7.9574.8210.14304Alief-7.7469.25-7.71219Alpine-2.1477.30-5.7251Alvarado6.1977.905.2312Alvin10.7383.7011.53159Amarillo0.2174.700.4789Anahuac3.7778.38-4.123Angleton13.4193.4511.8482Aransas County4.4479.406.72295Aransas Pass-7.0368.07-7.16306Arlington-8.0070.57-6.75289Athens-6.6166.47-2.7622Ballinger8.7588.036.26209Bandera-1.7274.572.271Bangs14.0291.5010.2053Barbers Hill6.1687.207.20175Bastrop-0.1672.70-3.5852Bay City6.1777.989.33136Bellville1.3678.05-3.8187Belton4.1481.934.39201Birdville-1.4081.32-1.4018Bishop Cons9.5787.205.70102Bloomington3.1376.101.5693Boerne3.6282.126.44120Borger2.1678.005.63137Brady1.3579.473.296Brazosport11.7891.4010.08109Breckenridge2.6878.57-1.30299Brenham-7.2367.97-2.69180Bridgeport-0.4977.202.79125Brooks County2.0372.433.33258Brownfield-4.4368.57-7.81228Brownsville-2.6473.20-2.21210Brownwood-1.7873.950.43225Bryan-2.4671.85-1.2811Burnet Cons10.8685.326.3255Calallen6.0486.778.01121Caldwell2.1578.55-1.2219Calhoun County9.4185.787.35186Cameron-0.7577.25-4.13252Canutillo-4.0471.07-0.0356Canyon6.0085.904.74254Carrizo Springs Cons-4.0969.20-1.35220Carrollton-Farmers Branch-2.1676.18-2.45307Castleberry-8.2864.28-7.09280Cedar Hill-5.8975.12-5.68334Center-14.9360.53-11.53200Channelview-1.3573.903.74333Chapel Hill-13.4260.45-12.2094Childress3.6181.228.95155Clear Creek0.4381.85-3.19302Cleburne-7.4869.80-6.65335Cleveland-17.1553.10-17.50151Clifton0.7179.552.81184Clint-0.6773.62-0.4316Coleman9.6286.026.49187College Station-0.7982.95-2.54213Colorado-1.9876.45-4.5114Columbia-Brazoria10.1688.1011.74282Columbus-5.9873.18-9.16146Comal0.9578.820.14107Comanche2.7981.18-2.62100Comfort3.3178.753.89185Connally-0.6877.60-1.74250Conroe-3.8874.10-1.5283Copperas Cove4.4383.603.49179Corpus Christi-0.4275.65-1.28178Corrigan-Camden-0.3072.974.85239Corsicana-3.3570.03-1.81324Cotulla-10.1761.10-8.78157Crosby0.2478.724.2662Crowley5.4388.32-0.82279Crystal City-5.6762.15-7.40139Cuero1.3379.689.32193Cypress-Fairbanks-1.0479.97-2.9999Dalhart3.3177.905.24332Dallas-13.2962.45-8.77222Decatur-2.2275.30-2.53133Deer Park1.5781.624.297Del Valle11.7778.5711.87262Denton-4.8069.57-2.1734Denver City7.5687.256.19269Devine-5.2672.20-7.75127Diboll1.9274.880.13242Dickinson-3.4666.78-2.33198Dimmitt-1.3072.100.83312Donna-8.6660.72-8.36288Dublin-6.5867.72-10.7440Dumas6.9480.558.33143Duncanville0.9878.050.78253Eagle Mt-Saginaw-4.0473.78-2.4336Eagle Pass7.5378.505.12263East Central-4.8574.90-4.50194East Chambers-1.0975.93-9.5846Eastland6.6684.823.11236Ector County-3.1368.970.21182Edcouch-Elsa-0.6075.70-3.8868Edgewood4.9275.154.06103Edinburg Cons3.0476.103.44173Edna-0.1477.322.0037El Campo7.5385.475.62300El Paso-7.3468.68-7.61293Elgin-6.6667.53-12.06207Ennis-1.6876.78-0.5991Everman3.6482.451.49256Fabens-4.2567.65-5.68249Farmersville-3.8277.12-0.4815Ferris9.9984.409.07106Floresville2.8776.974.4295Flour Bluff3.6082.854.44294Floydada-6.8266.43-5.74290Fort Bend-6.6475.82-7.04153Fort Worth0.4669.903.89292Fredericksburg-6.6671.72-7.7533Frenship7.7486.183.9290Frisco3.7381.382.62278Ft Stockton-5.6369.60-8.95311Gainesville-8.6167.55-6.6417Galena Park9.6181.979.9938Galveston7.3576.207.71205Garland-1.5375.00-1.7141Gatesville6.9285.157.74117George West2.2680.802.60326Georgetown-12.1069.65-6.51122Giddings2.1180.122.93297Glen Rose-7.2175.80-9.6069Goliad4.8883.655.40321Gonzales-9.4063.95-3.0261Goose Creek Cons5.6780.405.13115Graham2.4381.820.13237Grand Prairie-3.1373.35-3.872Grand Saline13.4388.0714.0972Grape Creek4.6979.12-1.62232Greenville-2.7268.651.31149Greenwood0.8282.603.61111Gregory-Portland2.5084.88-0.2244Groesbeck6.7781.0511.05108Harlandale2.7376.656.5684Harlingen Cons4.3882.574.12238Hays Cons-3.2472.68-0.80328Hearne-12.2863.65-19.78296Hempstead-7.2068.88-4.55318Henderson-9.1167.50-8.5225Hereford8.4282.788.3213Hidalgo10.3185.0510.4850Hillsboro6.3277.882.09330Hitchcock-12.7962.20-16.63183Hondo-0.6172.35-1.05202Houston-1.4169.882.01114Hudson2.4479.530.21259Humble-4.6477.45-5.23195Huntsville-1.1375.28-3.56223Hurst-Euless-Bedford-2.3480.18-0.37192Ingleside-0.9875.550.34308Ingram-8.4569.47-6.65174Irving-0.1576.80-1.50325Jacksonville-11.2759.62-1.3357Jim Hogg County5.9983.902.31191Jourdanton-0.9675.074.17261Judson-4.6774.78-5.50197Katy-1.2583.45-1.5739Kaufman7.0881.072.6477Kennedale4.5582.553.14317Kermit-9.0464.57-4.5558Kerrville5.9382.058.47229Killeen-2.6677.78-5.7492Kingsville3.6378.472.97286Klein-6.3078.30-2.9242La Feria6.8885.804.74131La Grange1.6777.126.4045La Joya6.7173.9512.074La Marque12.2083.509.00152La Porte0.6480.680.3766La Vega5.1376.501.98275La Vernia-5.4276.80-4.92199Lake Travis-1.3380.572.84265Lake Worth-4.9861.88-6.17135Lamar Cons1.4477.970.83274Lamesa-5.3766.30-0.83268Lampasas-5.2371.75-4.08230Lancaster-2.6669.821.26301Laredo-7.4369.20-5.83211Leander-1.8377.30-2.36266Lewisville-5.1277.93-8.10287Liberty-6.5570.15-3.8164Liberty Hill5.2184.404.64233Little Elm-3.0667.12-13.25101Littlefield3.2976.851.86316Livingston-8.9865.28-0.5896Llano3.5683.574.81188Longview-0.8472.18-3.398Los Fresnos Cons11.7489.577.78163Lubbock0.1676.500.8567Lubbock-Cooper5.0686.757.22226Lufkin-2.4873.050.67285Luling-6.2467.97-6.14267Lyford Cons-5.1969.30-7.29140Lytle1.1971.35-6.35167Madisonville Cons0.0774.782.60313Magnolia-8.6765.35-8.75329Manor-12.5158.35-14.00130Mansfield1.7283.12-0.39181Marble Falls-0.5174.503.3685Marion4.3585.303.39331Marlin-12.9659.45-13.73255Mathis-4.2065.65-6.5076McAllen4.5580.553.0354McGregor6.0887.322.01150McKinney0.7574.359.47320Medina Valley-9.3166.30-8.60241Mercedes-3.4473.35-2.2924Merkel8.5188.258.11169Mesquite-0.0178.53-3.2648Mexia6.5882.18-0.85273Midland-5.3770.05-0.71246Midlothian-3.7179.07-4.73132Mineola1.5978.820.0278Mineral Wells4.5277.453.3786Mission Cons4.3382.654.349Monahans-Wickett-Pyote11.5290.3210.96323Mount Pleasant-10.0861.50-9.225Mount Vernon12.1990.1811.8773Muleshoe4.6679.823.32319Nacogdoches-9.2965.43-12.19165Natalia0.1273.43-11.99160Navasota0.1671.88-0.23204Needville-1.5080.531.91244New Braunfels-3.6474.18-3.40124New Caney2.0575.534.09154North East0.4480.951.15298North Forest-7.2162.55-8.98218Northside-2.1377.35-2.05214Odem-Edroy-1.9977.40-8.0432Orange Grove7.8485.0010.12118Palacios2.2082.725.01281Palestine-5.9468.28-7.09172Pampa-0.0776.68-2.10126Pasadena1.9878.951.6943Pearland6.7788.454.74164Pearsall0.1473.25-1.21110Pecos-Barstow-Toyah2.5974.056.81144Perryton0.9777.30-0.01171Pflugerville-0.0682.620.0997Pharr-San Juan-Alamo3.3978.472.82272Pilot Point-5.3470.57-0.21176Pine Tree-0.2075.621.2728Pittsburg8.0281.620.5631Plainview7.8780.656.64123Pleasanton2.0875.473.9321Point Isabel9.1283.505.1898Port Arthur3.3268.471.84310Poteet-8.5565.72-5.21105Presidio2.9265.759.98177Princeton-0.2971.973.39142Progreso1.1170.405.4147Raymondville6.6178.686.01303Red Oak-7.7372.32-2.07148Rice Cons0.9373.97-7.18305Richardson-7.8672.03-6.12247Rio Grande City Cons-3.7966.80-3.6560Rio Hondo5.7582.651.2588Robinson3.9587.250.7671Robstown4.7376.552.69248Rockdale-3.8074.62-6.20277Roma-5.5964.05-4.42141Roosevelt1.1677.600.22221Round Rock-2.1979.07-3.01196Royal-1.1371.882.9975Royse City4.5678.604.32276San Angelo-5.4671.25-6.41309San Antonio-8.5067.70-6.6920San Benito Cons9.3582.588.65322San Diego-9.4161.60-11.09327San Elizario-12.1062.00-6.90216San Felipe-Del Rio Cons-2.0274.72-3.9159San Marcos Cons5.8980.255.22212Santa Fe-1.9775.951.63224Santa Rosa-2.4373.622.02208Schertz-Cibolo-U City-1.7077.152.46170Sealy-0.0678.25-0.46257Seguin-4.3169.400.78158Shallowater0.2278.98-4.2949Sharyland6.5184.728.48314Sheldon-8.6968.10-8.20283Sherman-6.1769.18-4.63104Sinton3.0376.285.05231Slaton-2.7175.000.32240Smithville-3.4169.553.21119Snyder2.1980.051.66147Socorro0.9576.50-0.16138Somerset1.3476.32-0.70206South San Antonio-1.5676.77-0.4463South Texas5.3693.48-0.32234Southside-3.0765.620.71112Southwest2.4774.004.17251Spring-4.0378.70-1.18235Spring Branch-3.1271.281.34260Stafford MSD-4.6673.85-7.51168Stephenville0.0580.93-1.2030Sweeny7.8988.986.19161Sweetwater0.1676.18-0.67145Taft0.9674.650.46243Tatum-3.5772.47-6.84217Taylor-2.0372.50-8.62245Teague-3.6578.65-2.48291Temple-6.6569.88-6.4365Terrell5.1578.202.0070Texas City4.7881.952.91128Tomball1.7880.051.50190Troy-0.9278.780.70156Tulia0.2876.70-0.9935Tuloso-Midway7.5383.203.77270Tyler-5.2970.101.7874United4.6273.954.79203Uvalde Cons-1.4470.102.5310Valley 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