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Policy Analysis No. 854
Fixing the Bias in Current State K–12 Education Rankings
By Stan Liebowitz and Matthew L. Kelly
State education rankings published by U.S. News & World Report, Education Week, and others play a prominent role in legislative debate and public discourse concerning education. These rankings are based partly on achievement tests, which measure student learning, and partly on other factors not directly related to student learning. When achievement tests are used as measures of learning in these conventional rankings, they are aggregated in a way that provides misleading results. To overcome these deficiencies, we create a new ranking of state education systems using demographically disaggregated achievement data and excluding less informative factors that are not directly related to learning. Using our methodology changes the order of state rankings considerably. Many states in New England and the Upper Midwest fall in the rankings, whereas many states in the South and Southwest score much higher-than they do in conventional rankings. Furthermore, we create another set of rankings on the efficiency of education spending. In these efficiency rankings, achieving successful outcomes while economizing on education expenditures is considered better than doing so through lavish spending. These efficiency rankings cause a further increase in the rankings of southern and western states and a decline in the rankings of northern states. Finally, our regression results indicate that unionization has a powerful negative influence on educational outcomes, and that, given current spending levels, additional spending has little effect. We also find no evidence of a relationship between student performance and teacher-pupil ratios or private school enrollment, but some evidence that charter school enrollment has a positive effect.
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Which states have the best K-12 education systems? What set of government policies and education spending levels is needed to achieve targeted outcomes in an efficient manner? Answers to these important questions are essential to the performance of our economy and country. Local workforce education and quality of schools are key determinants in business and residential location decisions. Determining which education policies are most cost-effective is also crucial for state and local politicians as they allocate limited taxpayer resources.
Several organizations rank state K-12 education systems, and these rankings play a prominent role in both legislative debate and public discourse concerning education. The most popular are arguably those of U.S. News & World Report (U.S. News).1. It is common for activists and pundits (whether in favor of homeschooling, stronger teacher unions, core standards, etc.) to use these rankings to support their arguments for changes in policy or spending priorities. As shown by the recent competition for Amazon's HQ2 (second headquarters), politicians and business leaders will also frequently cite education rankings to highlight their states' advantages.2. Recent teacher strikes across the country have likewise drawn renewed attention to education policy, and journalists inevitably mention state rankings when these topics arise.3. It is therefore important to ensure that such rankings accurately reflect performance.
Though well-intentioned, most existing rankings of state K-12 education are unreliable and misleading. The most popular and influential state education rankings fail to provide an "apples to apples" comparison between states.4. By treating states as though they had identical students, they ignore the substantial variation present in student populations across states. Conventional rankings also include data that are inappropriate or irrelevant to the educational performance of schools. Finally, these analyses disregard government budgetary constraints. Not surprisingly, using disaggregated measures of student learning, removing inappropriate or irrelevant variables, and examining the efficiency of educational spending reorders state rankings in fundamental ways. As we show in this report, employing our improved ranking methodology overturns the apparent consensus that schools in the South and Southwest perform less well than states in the Northeast and Upper Midwest. It also puts to rest the claim that more spending necessarily improves student performance.5.
Many rankings, including those of U.S. News, provide average scores on tests administered by the National Assessment of Education Progress (NAEP), sometimes referred to as "the nation's report card."6. The NAEP reports provide average scores for various subjects, such as math, reading, and science, for students at various grade levels.7. These scores are supposed to measure the degree to which students understand these subjects. While U.S. News includes other measures of education quality, such as graduation rates and SAT and ACT college entrance exam scores, direct measures of the entire student population's understanding of academic subject matter, such as those from the NAEP, are the most appropriate measures of success for an educational system.8. Whereas graduation is not necessarily an indication of actual learning, and only those students wishing to pursue a college degree tend to take standardized tests like the SAT and ACT, NAEP scores provide standardized measures of learning covering the entire student population. Focusing on NAEP data thus avoids selection bias while more closely measuring a school system's ability to improve actual student performance.
However, student heterogeneity is ignored by U.S. News and most other state rankings that use NAEP data as a component of their rankings. Students from different socioeconomic and ethnic backgrounds tend to perform differently (regardless of the state they are in). As this report will show, such aggregation often renders conventional state rankings as little more than a proxy for a jurisdiction's demography. This problem is all the more unfortunate because it is so easily avoided. NAEP provides demographic breakdowns of student scores by state. This oversight substantially skews the current rankings.
Perhaps just as problematic, some education rankings conflate inputs and outputs. For instance, Education Week uses per pupil expenditures as a component in its annual rankings.9. When direct measures of student achievement are used, such as NAEP scores, it is a mistake to include inputs, such as educational expenditures, as a separate factor.10. Doing so gives extra credit to states that spend excessively to achieve the same level of success others achieve with fewer resources, when that wasteful extra spending should instead be penalized in the rankings.
Our main goal in this report is to provide a ranking of public school systems in U.S. states that more accurately reflects the learning that is taking place. We attempt to move closer to a "value added" approach as explained in the following hypothetical. Consider one school system where every student knows how to read upon entering kindergarten. Compare this to a second school system where students don't have this skill upon entering kindergarten. It should come as no surprise if, by the end of first grade, the first school's students have better reading scores than the second school's. But if the second school's students improved more, relative to their initial situation, a value-added approach would conclude that the second system actually did a better job. The value-added approach tries to capture this by measuring improvement rather than absolute levels of education achievement. Although the ranking presented here does not directly measure value added, it captures the concept more closely than do previous rankings by accounting for the heterogeneity of students who presumably enter the school system with different skills. Our approach is thus a better way to gauge performance.
Moreover, this report will consider the importance of efficiency in a world of scarce resources. Our final rankings will rate states according to how much learning similar students have relative to the amount of resources used to achieve it.
The Impact of Heterogeneity
Students arrive to class on the first day of school with different backgrounds, skills, and life experiences, often related to socioeconomic status. Assuming away these differences, as most state rankings implicitly do, may lead analysts to attribute too much of the variation in state educational outcomes to school systems instead of to student characteristics. Taking student characteristics into account is one of the fundamental improvements made by our state rankings.
An example drawn from NAEP data illustrates how failing to account for student heterogeneity can lead to grossly misleading results. (For a more general demonstration of how heterogeneity affects results, see the Appendix.) According to U.S. News, Iowa ranks 8th and Texas ranks 33rd in terms of pre-K-12 quality. U.S. News includes only NAEP eighth-grade math and reading scores as components in its ranking, and Iowa leads Texas in both. By further including fourth grade scores and the NAEP science tests, the comparison between Iowa and Texas remains largely unchanged. Iowa students still do better than Texas students, but now in all six tests reported for those states (math, reading, and science in fourth and eighth grades). To use a baseball metaphor, this looks like a shut-out in Iowa's favor.
But this is not an apples-to-apples comparison. The characteristics of Texas students are very different from those of Iowa students; Iowa's student population is predominantly white, while Texas's is much more ethnically diverse. NAEP data include average test scores for various ethnic groups. Using the four most populous ethnic groups (white, black, Hispanic, and Asian),11. at two grade levels (fourth and eighth), and three subject-area tests (math, reading, science), there are 24 disaggregated scores that could, in principle, be compared between the two states in 2017. This is much more than just the two comparisons—eighth grade reading and math—that U.S. News considers.12.
Given that Iowa students outscore their Texas counterparts on each of the three tests in both fourth and eighth grades, one might reasonably expect that most of the disaggregated groups of Iowa students would also outscore their Texas counterparts in most of the twenty exams given in both states.13. But the exact opposite is the case. In fact, Texas students outscore their Iowa counterparts in all but one of the disaggregated comparisons. The only instance where Iowa students beat their Texas counterparts is the reading test for eighth grade Hispanic students. This is indeed a near shut-out, but one in Texas's favor, not Iowa's.
Let that sink in. Texas whites do better than Iowa whites in each subject test for each grade level. Similarly, Texas blacks do better than Iowa blacks in each subject test and grade level. Texas Hispanics do better than Iowa Hispanics in all but one test in one grade level. Texas Asians do better than Iowa Asians in all tests that both states report in common. In what sense could we possibly conclude that Iowa does a better job educating its students than does Texas?14. We think it obvious that the aggregated data here are misleading. The only reason for Iowa's higher overall average scores is that, compared to Texas, its student population is disproportionately composed of whites. Iowa's high ranking is merely a statistical artifact of a flawed measurement system. When student heterogeneity is considered, Texas schools clearly do a better job educating students, at least as indicated by the performance of students as measured by NAEP data.
This discrepancy in scores between these two states is no fluke either. In numerous instances, state education rankings change substantially when we take student heterogeneity into account.15. The makers of the NAEP, to their credit, allow comparisons to be made for heterogeneous subgroups of the student population. However, almost all the rankings fail to utilize these useful data to correct for this problem. This methodological oversight skews previous rankings in favor of homogeneously white states. In constructing our ranking, we will use these same NAEP data, but break down scores into the aforementioned 24 categories by test subject, grade, and ethnic group to more properly account for heterogeneity.
Importantly, we wish to make clear that our use of these four racial categories does not imply that differences between groups are in any way fixed or would not change under different circumstances. Using these categories to disaggregate students has the benefit of simplicity while also largely capturing the effects of other important socioeconomic variables that differ markedly between ethnic groups (and also between students within these groups).16. Such socioeconomic factors are related to race in complex ways, and controlling for race is common in the economic literature. In addition, by giving equal weight to each racial category, our procedure puts a greater emphasis on how well states teach each category of students than do traditional rankings, paying somewhat greater attention to how groups that have historically suffered from discrimination are faring.
A State Ranking of Learning That Accounts for Student Heterogeneity
Our methodology is to compare state scores for each of three subjects (math, reading, and science), four major ethnic groups (whites, blacks, Hispanics, and Asian/Pacific Islanders) and two grades (fourth and eighth),17. for a total of 24 potential observations in each state and the District of Columbia. We exclude factors such as graduation rates and pre-K enrollment that do not measure how much students have learned.
We give each of the 24 tests18. equal weight and base our ranking on the average of the test scores.19. This ranking is thus limited to measuring learning and does so in a way that avoids the aggregation fallacy. We refer to this as the "quality" rank.
From left to right, Table 1 shows our ranking using disaggregated NAEP scores ("quality ranking"), then how rankings would look if based solely on aggregate state NAEP test scores ("aggregated rank"), and finally the U.S. News rankings.
State rankings using disaggregated NAEP scores
*Controls for heterogeneity; **Does not control for heterogeneity.
Source: National Center for Education Statistics, 2017 NAEP Mathematics and Reading Assessments, https://www.nationsreportcard.gov/reading_math_2017_highlights/.
The difference between the aggregated rankings and the U.S. News rankings shows the effect of U.S. News' use of only partial NAEP data—no fourth grade or science scores—and the inclusion of factors unrelated to learning (e.g., graduation rates). The effects are substantial.
The difference between the disaggregated quality rank (first column) and the aggregated rank (third column) shows the effects of controlling for heterogeneity—our focus in this report—which are also substantial. States with small minority population shares (defined as Hispanic or black) tend to fall in the rankings when the data are disaggregated, and states with high shares of minority populations tend to rise when the data are disaggregated.
There are substantial differences between our quality rankings and the U.S. News rankings. For example, Maine drops from 6th in the U.S. News ranking to 49th in the quality ranking. Florida, which ranks 40th in U.S. News', jumps to 3rd in our quality ranking.
Maine apparently does very well in the nonlearning components of U.S. News' rankings; its aggregated NAEP scores would put it in 24th place, 18 positions lower than its U.S. News rank. But the aggregated NAEP scores overstate what its students have learned; Maine's quality ranking is a full 25 positions below that. On the 10 achievement tests reported for Maine, its rankings on those tests are 46th, 45th, 48th, 37th, 41st, 40th, 34th, 40th, 41st, and 23rd. It is astounding that U.S. News could rank Maine as high as 6th, given the deficient performance of both its black and white students (the only two groups reported for Maine) relative to black and white students in other states. But since Maine's student population is about 90 percent white, the aggregated scores bias the results upward.
On the other hand, Florida apparently scores poorly on U.S. News' nonlearning attributes, since its aggregated NAEP scores (ranked 16th) are much better than its U.S. News score (ranked 40th). Florida's student population is about 60 percent nonwhite, meaning that the aggregate scores are likely to underestimate Florida's education quality, which is borne out by the quality ranking. In fact, Florida gets considerably above-average scores for all but one of its 24 reported tests, with student performance on half of its tests among the top five states, which is how it is able to earn a rank of 3rd in our quality rankings.20.
The decline in Maine's ranking is representative of some other New England and midwestern states such as Vermont, New Hampshire, and Minnesota, which tend to have largely white populations, leading to misleadingly high positions in typical rankings such as U.S. News'. The increase in Florida's ranking mirrors gains in the rankings of other southern and southwestern states, such as Texas and Georgia, with large minority populations. This leads to a serious distortion of beliefs about which parts of the country do a better job educating their students.
We should note that the District of Columbia, which is not ranked at all by U.S. News, does very well in our quality rankings. It is not surprising that D.C.'s disaggregated ranking is quite different from the aggregated ranking, given that D.C.'s population is about 85 percent minority. Nevertheless, we suspect that the very large change in rank is something of an aberration. D.C.'s high ranking is driven by the unusually outstanding scores of its white students, who come from disproportionately affluent and educated families,21. and whose scores were more than four standard deviations above the national white mean in each test subject they participated in (a greater difference than for any other single ethnic group in any state). Were it not for these scores, D.C. would be somewhat below average (with D.C. blacks slightly below the national black average and Hispanics considerably below their average).
Massachusetts and New Jersey, which are highly ranked by U.S. News, are also highly ranked by our methodology, indicating that they deserve their high rankings based on the performance of all their student groups. Other states have similar placements in both rankings. Overall, however, the correlation between our rankings and U.S. News' rankings is only 0.35, which, while positive, does not evince a terribly strong relationship.
Failing to disaggregate student-performance data and inserting factors not related to learning distorts results. By construction, our measure better reflects the relative performance of each group of students in each state, as measured by the NAEP data. We believe the differences between our rankings and the conventional rankings warrant a serious reevaluation of which state education systems are doing the best jobs for their students; we hope the conventional ranking organizations will be prompted to make changes that more closely follow our methodology.
Examining the Efficiency of Education Expenditures
The overall quality of a school system is obviously of interest to educators, parents, and politicians. However, it's also important to consider, on behalf of taxpayers, the amount of government expenditure undertaken to achieve a given level of success. For example, New York spends the most money per student ($22,232), almost twice as much as the typical state. Yet that massive expenditure results in a rank of only 31 in Table 1. Tennessee, on the other hand, achieves a similar level of success (ranked 30th) and spends only $8,739 per student. Although the two states appear to have education systems of similar quality, the citizens of Tennessee are getting far more bang for the buck.
To show the spending efficiency of a state's school system, Figure 1 plots per student expenditures on the horizontal axis against student performance on the vertical axis. Notice that New York and Tennessee are at about the same height but that New York is much farther to the right.
Scatterplot of per pupil expenditures and average normalized NAEP test scores
The most efficient educational systems are seen in the upper-left corner of Figure 1, where systems are high quality and inexpensive. The least efficient systems are found in the lower right. From casual examination of Figure 1, it appears likely that some states are not using education funds efficiently.
Because spending values are nominal—that is, not adjusted for cost-of-living differences across states—using unadjusted spending figures might disadvantage high-cost states, in which above-average education costs may reflect price differences rather than more extravagent spending. For this reason, we also calculate a ranking based on education quality per adjusted dollar of expenditure, where the adjustment controls for statewide differences in the cost of living (COL).22. The COL-adjusted rankings are probably the rankings that best reflect how efficiently states are providing education. Adjusting for COL has a large effect on high-cost states such as Hawaii, California, and D.C. Table 2 presents two spending-efficiency rankings of states that capture how well their heterogeneous students do on NAEP exams in comparison to how much the state spends to achieve those rankings. These rankings are calculated by taking a slightly revised version of the state's z-score and dividing it by the nominal dollar amount of educational expenditure or by the COL-adjusted educational expenditure made by the state.23. These adjustments lower the rank of states like New York, which spends a great deal for mediocre performance, and increase the rank of states like Tennessee, which achieves similar performance at a much lower cost. Massachusetts and New Jersey, which impart a good deal of knowledge to their students, do so in such a costly manner using nominal values that they fall out of the top 20, although Massachusetts, having a higher cost of living, remains in the top 20 when the cost of living adjustment is made. States like Idaho and Utah, which achieve only mediocre success in imparting knowledge to students, do it so inexpensively that they move up near the top 10.
State rankings adjusted for student heterogeneity and expenditures
*COL = cost of living.
**Using nominal dollars.
Sources: National Center for Education Statistics, 2017 NAEP Mathematics and Reading Assessments, https://www.nationsreportcard.gov/reading_math_2017_highlights/; and Missouri Economic Research and Information Center, Cost of Living Data Series 2017 Annual Average, https://www.missourieconomy.org/indicators/cost_of_living.
The top of the efficiency ranking is dominated by states in the South and Southwest. This result is quite a difference from the traditional rankings.
The correlation between these spending efficiency rankings and the U.S. News rankings drops to -0.14 and -0.06 for the nominal and COL-adjusted efficiency rankings, respectively. This drop is not surprising since the rankings in Table 2 treat expenditures as something to be economized on, whereas the U.S. News rankings don't consider K-12 expenditures at all (and other rankings consider higher expenditures purely as a plus factor). The correlations of the Table 1 quality rankings and Table 2 efficiency rankings, with nominal and adjusted expenditures, are 0.54 and 0.65, respectively. This indicates that accounting for the efficiency of expenditures substantially alters the rankings, although somewhat less so when the cost of living is adjusted for. This higher correlation for the COL rankings makes sense because high-cost states devoting the same share of resources as the typical state would be expected to spend above-average nominal dollars, and the COL adjustment reflects that.
Other Factors Possibly Related to Student Performance
Our data allow us to make a brief analysis of some factors that might be related to student performance in states. Our candidate factors are expenditure per student (either nominal or COL adjusted), student-teacher ratios, the strength of teacher unions, the share of students in private schools, and the share in charter schools.24. The expenditure per student variable is considered in a quadratic form since diminishing marginal returns is a common expectation in economic theory.
Table 3 presents the summary statistics for these variables. The average z-score is close to zero, which is to be expected.25. Nominal expenditure per student ranges from $6,837 to $22,232, with the COL-adjusted values having a somewhat smaller range. The union strength variable is merely a ranking from 1 to 51, with 51 being the state with the most powerful union effect. The number of students per teacher ranges from a low of 10.54 to a high of 23.63. The other variables are self-explanatory.
Sources: National Center for Education Statistics, 2017 NAEP Mathematics and Reading Assessments, https://www.nationsreportcard.gov/reading_math_2017_highlights/; Missouri Economic Research and Information Center, Cost of Living Data Series 2017 Annual Average, https://www.missourieconomy.org/indicators/cost_of_living; National Center for Education Statistics, Digest of Education Statistics: 2017, Table 236.65, https://nces.ed.gov/programs/digest/d17/tables/dt17_236.65.asp?current=yes; Amber M. Winkler, Janie Scull, and Dara Zeehandelaar, "How Strong are Teacher Unions? A State-By-State Comparison," Thomas B. Fordham Institute and Education Reform Now, 2012; Digest of Education Statistics: 2017, Table 208.40, https://nces.ed.gov/programs/digest/d17/tables/dt17_208.40.asp?current=yes; National Center for Education Statistics, Private School Universe Survey, https://nces.ed.gov/surveys/pss/; charter school share determined by dividing the total enrollment in charter schools by the total enrollment in all public schools for each state, Digest of Education Statistics: 2017, Table 216.90, https://nces.ed.gov/programs/digest/d17/tables/dt17_216.90.asp?current=yes, and Digest of Education Statistics: 2016, Table 203.20, https://nces.ed.gov/programs/digest/d16/tables/dt16_203.20.asp.; and Education Commission of the States, "50-State Comparison: Vouchers," March 6, 2017, http://www.ecs.org/50-state-comparison-vouchers/.
We use multiple regression analysis to measure the relationship between these variables and our (dependent) variable—the average z-scores drawn from state NAEP test scores in the 24 categories mentioned above. Regression analysis can show how variables are related to one another but cannot demonstrate whether there is causality between a pair of variables where changes in one variable lead to changes in another variable.
Table 4 provides the regression results using COL expenditures (results on the left) or using nominal expenditures (results on the right). To save space, we only include the coefficients and p-values, the latter of which, when subtracted from one, provides statistical confidence levels. Those coefficients for variables that were statistically significant are marked with asterisks (one asterisk indicates a 90 percent confidence level and two a level of 95 percent).
Multiple regression results explaining quality of education
The choice of nominal vs. COL expenditures leads to a large difference in the results. The COL-adjusted results are likely to lead to a greater number of correct conclusions.
Nominal expenditures per student are related in a positive and statistically significant manner to student performance up to a point, but the positive effect of expenditures per student declines as expenditures per student increase. The coefficients on the two expenditure-per-student variables indicate that additional nominal spending is no longer related to performance when nominal spending gets to a level of $18,500 per student, a level that is exceeded by only a handful of states.26. The predicted decline in student performance for the few states exceeding the $18,500 limit, assuming causality from spending to performance, is quite small (approximately two rank positions for the state with the largest expenditure),27. so that this evidence is best interpreted as supporting a view that the states with the highest spending have reached a saturation point beyond which no more gains can be made.28.
Using COL-adjusted values, however, starkly changes results. With COL values, no significant relationship is found between spending and student performance, either in magnitude or statistical significance. This does not necessarily imply that spending overall has no effect on outcomes (assuming causality), but merely that most states have reached a sufficient level of spending such that additional spending does not appear to be related to achievement as measured by these test scores. This is a different conclusion from that based on nominal expenditures. These different results imply that care must be taken, not just to ensure that achievement test scores are disaggregated in analyses of educational performance, but also that if expenditures are used in such analyses, they are adjusted for cost of living differentials.
The union strength variable in Table 4 has a substantial and statistically significant negative relationship with student achievement. The coefficient in the nominal expenditure regressions suggests a relationship such that if a state went from having the weakest unions to the strongest unions, holding the other education factors constant, that state would have a decrease in its z-score of over 1.22 (0.024 × 51). To put this in perspective, note in Table 3 that the z-scores vary from a high of 1.22 to a low of -1.51, a range of 2.73. Thus, the shift from weakest to strongest unions would move a state down about 45 percent of the way through this total range, or equivalently, alter the rank of the state by about 23 positions.29. This is a dramatic result. The COL regressions also show a large relationship, but it is only about half the magnitude of the coefficient in the nominal expenditure regressions. This negative relationship suggests an obvious interpretation. It is well known that teachers' unions aim to increase wages for their members, which may increase student performance if higher quality teachers are drawn to the higher salaries. Such a hypothesis is inconsistent with the finding here, which is instead consistent with the view that unions are negatively related to student performance, presumably by opposing the removal of underperforming teachers, opposing merit-based pay, or because of union work rules. While much of the empirical literature finds positive relationships between unionization and student performance, studies that most effectively control for heterogeneous student populations, as we have, tend to find more negative relationships, such as those found here.30.
Our results also indicate that having a greater share of students in charter schools is positively related to student achievement, with the result being statistically significant in the COL regressions but not in the nominal expenditure regressions. The size of the relationship is fairly small, however, indicating, if the relationship were causal, that when a state increases its share of students in charter schools from 0 to 50 percent (slightly above the level of the highest observation) it would be expected to have an increase in rank of only 0.9 positions (0.5 × 1.8) in the COL regression and about half of that in the nominal expenditure regressions (where the coefficient is not statistically significant).31. Given that there is great heterogeneity in charter schools both within and between states, it is not surprising that our rather simple statistical approach does not find much of a relationship.
We also find that the share of students in private schools has a small negative relationship with the performance of students in public schools, but the level of statistical confidence is far too low for these results to be given any credence. (Although private school students take the NAEP exam, the NAEP data we use are based only on public school students.) Similarly, the existence of vouchers appears to have a negative relationship to achievement, but the high p-values tell us we cannot have confidence in those results.
There is some slight evidence, based on the COL regression, that higher student-teacher ratios have a small negative relationship with student performance, but the level of statistical confidence is below normally accepted levels. Though having more students per teacher is theorized to be negatively related to student performance, the empirical literature largely fails to find consistent effects of student-teacher ratios and class size on student performance.32. We should not be too surprised that student-teacher ratios do not appear to have a clear relationship with learning since the student-teacher ratios used here are aggregated for entire states, merging together many different classrooms in elementary, middle, and high schools.
Some Limitations
Although this study constitutes a significant improvement on leading state education rankings, it retains some of their limitations.
If the makers of state education rankings were to be frank, they would acknowledge that the entire enterprise of ranking state-level systems is only a blunt instrument for judging school quality. There exists substantial variation in educational quality within states. Schools differ from district to district and within districts. We generally dislike the idea of painting the performance of all schools in a given state with the same brush. However, state-level rankings do provide an intuitively pleasing basis for lawmakers and interested citizens to compare state education policies. Because state rankings currently play such a prominent role in the public debate on education policy, their more glaring methodological defects detailed above demand rectification. Any state ranking is nonetheless limited by aggregation inherent at the state-level unit of analysis.
Another limitation to our study, common to virtually all state education rankings, is that we treat the result of education as a one-dimensional variable. Of course, educational results are multifaceted and more complex than a single measure could capture. A standardized test may not pick up potentially important qualities such as creativity, critical thinking, or grit. Part of the problem is that there is no accepted measurement of those attributes.
We also are using a data snapshot that reflects measures of learning at a particular moment in time. However, the performance of students at any grade level depends on their education at all prior grade levels. A ranking of states based on student performance is the culmination of learning over a lengthy time period. An implicit assumption in creating such rankings is that the quality of various school systems changes slowly enough for a snapshot in one year to convey meaningful information about the school system as it exists over the entire interval in which learning occurred. This assumption allows us to attribute current or recent student performance, which is largely based on past years of teaching, to the teaching quality currently found in these schools. This assumption is present in most state rankings but may obscure sudden and significant improvement, or deterioration, in student knowledge that occurs in discrete years.
While the state level may be too aggregated a unit of analysis for the optimal examination of educational outcomes, state rankings are frequently used and discussed. Whether based appropriately on learning outcomes or inappropriately on nonlearning factors, comparisons between states greatly influence the public discourse on education. When these rankings fail to account for the heterogeneity of student populations, however, they skew results in favor of states with fewer socioeconomically challenged students.
Our ranking corrects these problems by focusing on outputs and the value added to each of the demographic groups the state education system serves. Furthermore, we consider the cost-effectiveness of education spending in U.S. states. States that spend efficiently should be recognized as more successful than states paying larger sums for similar or worse outcomes.
Adjusting for the heterogeneity of students has a powerful effect on the assessments of how well states educate their students. Certain southern and western states, such as Florida and Texas, have much better student performances than appears to be the case when student heterogeneity is not taken into account. Other states, such as Maine and Rhode Island in New England, fall substantially. These results run counter to conventional wisdom that the best education is found in northern and eastern states with powerful unions and high expenditures.
This difference is even more pronounced when spending efficiency, a factor generally neglected in conventional rankings, is taken into account. Florida, Texas, and Virginia are seen to be the most efficient in terms of quality achieved per COL-adjusted dollar spent. Conversely, West Virginia, Alabama, and Maine are the least efficient. Some states that do an excellent job educating students, such as Massachusetts and New Jersey, also spend quite lavishly and thus fall considerably when spending efficiency is considered.
Finally, we examine some factors thought to influence student performance. We find evidence that state spending appears to have reached a point of zero returns and that unionization is negatively related to student performance, and some evidence that charter schools may have a small positive relationship to student achievement. We find little evidence that class size, vouchers, or the share of students in private schools have measurable effects on state performance.
Which state education systems are worth emulating and which are not? The conventional answer to this question deserves to be reevaluated in light of the results presented in this report. We hope that our rankings will better inform pundits, policymakers, and activists as they seek to improve K-12 education.
Conventional education-ranking methodologies based on NAEP achievement tests are likely to skew results. In this Appendix, we provide a simple example of how and why that happens.
Our example assumes two types of students and three types of schools (or state school systems). The two columns on the right in appendix Table 1 denote different types of student, and each row represents a different school. School B is assumed to be 10 percent better than School A, and School C is assumed to be 20 percent better than School A, regardless of the student type being educated.
There are two types of students; S2 students are better prepared than S1 students. Students of the same type score differently on standard exams depending on which school they are in, but the two student types also perform differently from each other no matter which school they attend. Depending on the proportions of each type of student in a given school, a school's rank may vary substantially if the wrong methodology is used.
Example of students and scores
Source: Author calculations.
An informative ranking should reflect each school's relative performance, and the scores on which the rankings are based should reflect the 10 percent difference between School A and School B, and the 20 percent difference between School A and School C. Obviously, a reliable ranking mechanism should place School A in 3rd place, B in 2nd, and C in 1st.
However, problems arise for the typical ranking procedure when schools have different proportions of student types. The appendix Table 2 shows results from a typical ranking procedure under two different population scenarios.
School ranking 1 shows what happens when 75 percent of School A's students are type S2 and 25 percent are type S1; School B's students are split 50-50 between types S1 and S2; and School C's students are 75 percent type S1 and 25 percent type S2.33.
Because School A has a disproportionately large share of the stronger S2 students, it scores above the other two schools even though School A is the weakest school. Ranking 1 completely inverts the correct ranking of schools. This example, detailed in appendix Table 2, demonstrates how rankings that do not take the heterogeneity of students and the proportions of each type of student in each school into account can give entirely misleading results.
Rankings not accounting for heterogeneity
Conversely, school ranking 2 reverses the student populations of schools A and C. School C now also has more of the strongest students. The rankings are correctly ordered, but the underlying data used for the rankings greatly exaggerate the superiority of School C. Comparing the scores of the three schools, School B appears to be 32 percent better than School A and School C appears to be 68 percent better than School A, even though we know (by construction) that the correct values are 10 percent and 20 percent, respectively. School ranking 2 only happens to get the order right because there are no intermediary schools whose rankings would be improperly altered by the exaggerated scores of schools A and C in ranking 2.
The ranking methodology used in this paper, by contrast, compares each school for each type of student separately. It measures quality by looking at the numbers in appendix Table 1 and noting that each type of student at School B scores 10 percent higher than the same type of student at School A, and each type of student at School C scores 20 percent higher than the same type of student at School A. That is what makes our methodology conceptually superior to prior methodologies.
If all schools happened to have the same share of different types of students, a possibility not shown in appendix Table 2, the conventional ranking methodology used by U.S. News would work as well as our rankings. But our analysis in this paper has shown that schools and school systems in the real world have very different student populations, which is why our rankings differ so much from previous rankings. Our general methodology isn't just hypothetically better under certain demographic assumptions; rather, it is better under any and all demographic circumstances.
1. "Pre-K-12 Education Rankings: Measuring How Well States Are Preparing Students for College," U.S. News & World Report, May 18, 2018, https://www.usnews.com/news/best-states/rankings/education/preK-12. Others include those by Wallet Hub, Education Week, and the American Legislative Exchange Council.
2. Govs. Phil Murphy of New Jersey and Greg Abbott of Texas recently sparred over the virtues and vices of their state business climates, including their education systems, in a pair of newspaper articles. Greg Abbott, "Hey, Jersey, Don't Move to Fla. to Avoid High Taxes, Come to Texas. Love, Gov. Abbott," Star-Ledger, April 17 2018, http://www.nj.com/opinion/index.ssf/2018/04/hey_jersey_dont_move_to_fla_to_avoid_high_taxes_co.html; and Phil Murphy, "NJ Gov. Murphy to Texas Gov. Abbott: Back Off from Our People and Companies," Dallas Morning News, April 18, 2018, https://www.dallasnews.com/opinion/commentary/2018/04/18/nj-gov-murphy-texas-gov-abbott-back-people-companies.
3. Bryce Covert, "Oklahoma Teachers Strike for a 4th Day to Protest Rock-Bottom Education Funding," Nation, April 5, 2018.
4. We are aware of an earlier discussion by Dave Burge in a March 2, 2011, posting on his "Iowahawk" blog, discussing the mismatch between state K-12 rankings with and without accounting for heterogeneous student populations, http://iowahawk.typepad.com/iowahawk/2011/03/longhorns-17-badgers-1.html. A 2015 report by Matthew M. Chingos, "Breaking the Curve," https://www.urban.org/research/publication/breaking-curve-promises-and-pitfalls-using-naep-data-assess-state-role-student-achievement, published by the Urban Institute, is a more complete discussion of the problems of aggregation and presents on a separate webpage updated rankings of states that are similar to ours, but it does not discuss the nature of the differences between its rankings and the more traditional rankings. Chingos uses more controls than just ethnicity, but the extra controls have only minor effects on the rankings. He also uses the more complete "restricted use" data set from the National Assessment of Education Progress (NAEP), whereas we use the less complete but more readily available public NAEP data. One advantage of our analysis, in a society obsessed with STEM proficiency, is that we use the science test in addition to math and reading, whereas Chingos only uses math and reading.
5. For a recent example of the spending hypothesis see Paul Krugman, "We Don't Need No Education," New York Times, April 23, 2018. Krugman approvingly cites California and New York as positive examples of states that have considerably raised teacher pay over the last two decades, implying that such states would do a better job educating students. As noted in this paper, both states rank below average in educating their students.
6. We assume, as do other rankings that use NAEP data, that the NAEP tests assess student performance on material that students should be learning and therefore reflect the success of a school system in educating its students. It is of course possible that standardized tests do not correctly measure educational success. This would be a particular problem if some schools alter their teaching to focus on doing well on those tests while other schools do not. We think this is less of a problem for NAEP tests because most grades and most teachers are not included in the sample, meaning that when teacher pay and school funding are tied to performance on standardized tests, they will be tied to tests other than NAEP.
7. Since 1969, the NAEP test has been administered by the National Center for Education Statistics within the U.S. Department of Education. Results are released annually as "the nation's report card." Tests in several subjects are administered to 4th, 8th, and sometimes 12th graders. Not every state is given every test in every year, but all states take the math and reading tests at least every two years. The National Assessment Governing Board determines which test subjects will be administered each year. In the analysis below, we use the most recent data for math and reading tests, from 2017, and the science test is from 2015. NAEP tests are not given to every student in every state, but rather, results are drawn from a sample. Tests are given to a sample of students within each jurisdiction, selected at random from schools chosen so as to reflect the overall demographic and socioeconomic characteristics of the jurisdiction. Roughly 20-40 students are tested from each selected school. In a combined national and state sample, there are approximately 3,000 students per participating jurisdiction from approximately 100 schools. NAEP 8th grade test scores are a component of U.S. News' state K-12 education rankings, but are highly aggregated.
8. As direct measures of student learning for the entire student body, NAEP scores should form the basis of any state rankings of education. Nevertheless, rankings such as U.S. News' include not only NAEP scores, but other variables that do not measure learning, such as graduation rates, pre-K education quality/enrollment, and ACT/SAT scores, which measure learning but are not, in many cases, taken by all students in a state and are likely to be highly correlated with NAEP scores. We believe that these other measures do not belong in a ranking of state education quality.
9. "Quality Counts 2018: Grading the States," Education Week, January 2018, https://www.edweek.org/ew/collections/quality-counts-2018-state-grades/index.html. The three broad components used in this ranking include "chance for success," "state finances," and "K-12 achievement."
10. Informed by such rankings, it's no wonder the public debate on education typically assumes more spending is always better, even in the absence of corresponding improvements in student outcomes.
11. NAEP data also include scores for the ethnic categories "American Indian/Native Alaskan," and "Two or More." However, too few states had sufficient data for these scores to be a reliable indicator of the performance of these groups in that state. These populations are small enough in number to exclude from our analysis.
12. Not all states give all the tests (e.g., science test) to their students. While every state must have students take the math and reading tests at least every two years, the National Assessment Governing Board determines which other tests will be given to which states.
13. Because Iowa lacks enough Asian fourth and eighth grade students to provide a reliable average from the NAEP sample, NAEP does not have scores for Asian fourth graders in any subject or Asian eighth graders in science. This lowers the number of possible tests in Iowa from 24 to 20.
14. Our rankings assume that students in each ethnic group are similar across states. Although this assumption may not always be correct, it is more realistic than the assumption made in other rankings that the entire student population is similar across states.
15. For example, Washington, Utah, North Dakota, New Hampshire, Nebraska, and Minnesota also shut out Texas on all six tests (math, reading, science, 4th and 8th grades) under the assumption of homogeneous student populations. Nevertheless, Texas dominates all these states when comparisons are made using the full set of 24 exams that allow for student heterogeneity. Six states change by more than 24 positions depending on whether they are ranked using aggregated or disaggregated NAEP scores.
16. There are other categories in the NAEP data not directly related to race. Several of these (e.g., disability status, English language learner status, gender) have only minuscule effects on rankings and thus are ignored in our analysis. Among these nonracial factors, the most important is whether the student qualifies for subsidized school lunches, a proxy for family income. We do not include this variable in our analysis because the income requirements determining which students qualify for subsidized lunches are the same for all states in the contiguous United States, despite considerable differences in cost of living between jurisdictions. High cost of living states can have costs 85 percent higher than low cost of living states. High cost of living states will have fewer students qualify for subsidized lunches, and low cost of living states will have more students qualify than would be the case if cost of living adjustments were made. Because the distribution of cost of living values across states is not symmetrical, the difference in scores between students with subsidized lunches and students without, across states, is likely to be biased. This bias is pertinent to our examination of state education systems and student performance, so we exclude it from our analysis. Its inclusion would only have had a minor effect on our rankings, however, since the correlation between a state ranking that includes this variable (at half the importance of the four equally weighted ethnicity variables) with one that excludes it is 0.92. A different nonracial variable is the parents' education level, but this variable has the deficiency of only being available for eighth grade and not fourth grade students.
17. While we would have preferred to include test scores for 12th grade students, the data were not sufficiently complete to do so. While the NAEP test is given to 12th graders, it was only given to a national sample of students in 2015, and the most recent state averages available are from 2013. Even these 2013 state averages did not have a sufficient number of students from many of the ethnic groups we consider, and many states lacked a large number of observations. Because of the relatively incomplete data for 12th graders, we chose to include only 4th and 8th grade test scores. Note that U.S. News only includes state averages for 8th grade math and reading tests in their rankings.
18. When states do not report scores for each of the 24 NAEP categories, those states have their average scores calculated based on the exams that are reported.
19. We equate the importance of each of the 24 tests by forming, for each of the 24 possible exams, a z-score for each state, under the assumption that these state test scores have a normal distribution. The z-statistic for each observation is the difference between a particular state's test score and the average score for all states, divided by the standard deviation of those scores over the states. Our overall ranking is merely the average z-score for each state. Thus, exams with greater variations or higher or lower mean scores do not have greater weight than any other test in our sample. The z-score measures how many standard deviations a state is above or below the mean score calculated over all states. One might argue that we should use an average weighted by the share of students, but we choose to give each group equal importance. If we had used population weights, the rankings would not have changed very much because the correlation between the two sets of scores is 0.86, and four of the top-five and four of the bottom-five states remain the same.
20. Without listing all of Florida's 24 scores, its lowest 5 (out of the 51 states, in reverse order) are ranked 27, 21, 20, 19, and 10. The rest are all ranked in the top 10, with 12 of Florida's test scores among the top 5 states.
21. Some 89 percent are college educated. See for example, David Alpert, "DC Has Almost No White Residents without College Degrees," GGW.org, August 29, 2016, https://ggwash.org/view/42563/dc-has-almost-no-white-residents-without-college-degrees-its-a-different-story-for-black-residents.
22. The statewide cost of living adjustments are taken from the Missouri Economic Research and Information Center's Cost of Living Data Series 2017 Annual Average, https://www.missourieconomy.org/indicators/cost_of_living.
23. It would be a mistake to use straightforward z-scores from Table 1 when constructing the "z-Score/$" variable because states with z-scores near zero and thus near one another would hardly differ even if their expenditures per student were very different. Instead, we added 2.50 to each z-score so that all states have positive z-scores and the lowest state would have a revised z-score of 1. We then divided each state's revised z-score by the expenditure per student to arrive at the values shown in Table 2.
24. Data on expenditures, student-teacher ratios, and share of students in charter schools are taken from the National Center for Education Statistics' Digest of Education Statistics. Data on share of students in private schools come from the NCES's Private School Universe Survey. Our variable for unionization is a 2012 ranking of states constructed by researchers at the Thomas B. Fordham Institute, an education research organization, that used 37 different variables in five broad categories (Resources and Membership, Involvement in Politics, Scope in Bargaining, State Policies, and Perceived Influence). The ranking can be found in Amber M. Winkler, Janie Scull, and Dara Zeehandelaar, "How Strong Are Teacher Unions? A State-By-State Comparison," Thomas B. Fordham Institute and Education Reform Now, 2012, https://edexcellence.net/publications/how-strong-are-us-teacher-unions.html.
25. Because many states had results for fewer than 24 exams, giving each state equal weight in the overall average would not provide the zero "average" that would be expected if the average of every z-score were used to form the average. There were also some rounding errors.
26. New Jersey, Vermont, Connecticut, Washington, D.C., Alaska, and New York all exceed this level.
27. The decline is 0.15 z-units, which is about 5 percent of the total z-score range.
28. We should also note that efficient use of money requires that it be spent up until the point where the marginal value of the benefits is less than the marginal expenditure. Thus, the point where increasing expenditures provides no additional value cannot be the efficient level of expenditure. Instead, the efficient level of expenditure must lie below that amount.
29. This is a somewhat rough approximation because the ranks form a uniform distribution and the z-scores form a normal distribution with the mass of observations near the mean. A movement of a given z-distance will change ranks more if the movement occurs near the mean than if the movement occurs near the tails.
30. For a review of the literature on unionization and student performance, see Joshua M. Cowen and Katharine O. Strunk, "The Impact of Teachers' Unions on Educational Outcomes: What We Know and What We Need to Learn," Economics of Education Review 48 (2015): 208-23. Earlier studies found positive effects of unionization, but recent studies are more mixed. Most researchers agree that unionization likely affects different types of students differently. For studies that find unionization negatively affects student performance, see Caroline Minter Hoxby, "How Teachers' Unions Affect Education Production," Quarterly Journal of Economics 111, no. 3 (1996): 671-718, https://doi.org/10.2307/2946669; and Geeta Kingdom and Francis Teal, "Teacher Unions, Teacher Pay and Student Performance in India: A Pupil Fixed Effects Approach," Journal of Development Economics 91, no. 2 (2010): 278-88, https://doi.org/10.1016/j. jdeveco.2009.09.001 For studies that find no effect of unionization, see Michael F. Lovenheim, "The Effect of Teachers' Unions on Education Production: Evidence from Union Election Certifications in Three Midwestern States," Journal of Labor Economics 27, no. 4 (2009): 525-87, https://doi.org/10.1086/605653. More recently, only very small negative effects on student performance were found in Bradley D. Mariano and Katharine O. Strunk, "The Bad End of the Bargain? Revisiting the Relationship between Collective Bargaining Agreements and Student Achievement," Economics of Education Review 65 (2018): 93-106, https://doi.org/10.1016/j.econedurev.2018.04.006.
31. To arrive at this value, we multiply the coefficient (1.96) by 50 percent to determine the change in z-score and then divide by 2.73, the range of z-scores among the states. This provides a value of 35.5 percent, indicating how much of the range in z-scores would be traversed as a result of the change in charter school students. This value is then multiplied by 51 states in the analysis.
32. For a discussion on the empirical literature regarding school class size, see Edward P. Lazear, "Educational Production," Quarterly Journal of Economics 116, no. 3 (2001): 777-803, https://doi.org/10.1162/00335530152466232. Lazear suggests that differing student and teacher characteristics make it difficult to isolate the effect of class size on student outcomes. This view, although spun in a more positive light, generally is supported in a more recent summary of the academic literature found in Grover J. Whitehurst and Matthew M. Chingos, "Class Size: What Research Says and Why It Matters for State Policy," Brown Center on Education Policy, Brookings Institution, May 2011, https://www.brookings.edu/research/class-size-what-research-says-and-what-it-means-for-state-policy/.
33. The score column in appendix Table 2 merely multiplies the score for each type of student at a school by the share of the student type in the school population and sums the amounts. For example, the 87.5 value for School A in ranking 1 is found by multiplying the S1 score of 50 by .25 (=12.5) and adding that to the product of the population share of S2 (0.75) and the S2 score of 100 (=75) in School A. This method is effectively what U.S. News and other conventional rankings use.
Stan Liebowitz is the Ashbel Smith Professor of Economics and director of the Center for the Analysis of Property Rights and Innovation at the Jindal School of Management, University of Texas at Dallas; he is also an adjunct fellow at the Cato Institute. Matthew Kelly is a graduate student and research fellow at the Colloquium for the Advancement of Free-Enterprise Education at the Jindal School of Management, University of Texas at Dallas


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Die Nationalbibliothek Griechenlands () ist die Nationalbibliothek Griechenlands. Ihr Sitz befindet sich seit 2016 in einem von Renzo Piano entworfenen Gebäude im Stavros Niarchos Foundation Cultural Center in Kallithea bei Athen. Zuvor befand sie sich in einem vom dänischen Architekten Theophil von Hansen als Teil seiner Athener Trilogie klassizistischer Gebäude einschließlich der Athener Akademie und dem Originalgebäude der Athener Universität entworfenen Gebäude im Athener Stadtzentrum.

Geschichte
Die ursprüngliche Idee einer Nationalbibliothek in Griechenland stammt von dem Philhellenen Johann Jakob Meyer. In einem Artikel seiner Zeitung Elleniká Chroniká vom August 1824 stritt er zusammen mit Lord Byron für die Griechische Unabhängigkeit. Meyers Idee wurde 1829 von der Griechischen Regierung durch Ioannis Kapodistrias umgesetzt, als dieser die Gründung der Nationalbibliothek neben anderen Bildungseinrichtungen wie Schulen und Museen anordnete.
Anfangs war die Bibliothek provisorisch im Waisenhaus der Insel Aegina untergebracht, die als Erziehungseinrichtung dem gleichen Ressort unterstand. Georgios Gennadios bemühte sich um den Aufbau des Bestandes. Ende 1830 betrug der Gesamtbestand 1018 Bücher. 1834 folgte der Umzug nach Athen.

1834 wurde die Bibliothek als Institution gegründet, sie war bis zur Fertigstellung des Gebäudes auf verschiedene Standorte verteilt, zu diesem Zeitpunkt hatte der Bestand die 1995 Bücher erreicht, Christoforos und Konstantinos Sakellarios schenkten weitere 5400 Bücher und Markos Renieris 3401 Bücher. 1842 betrug der Bestand ca. 15.000 Bücher. Sie befand sich im Universitätsgebäude, bis 1903 als der Umzug in das von Panayis Vagliano gestiftete Gebäude erfolgte. Von 1877 bis 1910 war der Altphilologe Michael Deffner Direktor der Bibliothek.

Vor dem ehemaligen Bibliotheksgebäude steht die von Georgios Bonanos gestaltete Statue von Panayis Vagliano, einem Mäzen der Bibliothek.

Im Juni 2016 zog die Nationalbibliothek in das seit 2006 in Planung befindliche und von Renzo Piano entworfene Gebäude des Stavros Niarchos Foundation Cultural Center in Kallithea. Ebenfalls dort untergebracht ist die Nationaloper von Griechenland.

Handschriftensammlung
Die Bibliothek besitzt 4500 griechische Manuskripte und ist damit eine der größten Sammlungen griechischer Schriften.

In der Bibliothekssammlung befindet sich ein Kodex der vier Evangelien, die dem Schreiber Matthäus zugeordnet werden, eine Unzialhandschrift mit einem Fragment des Matthäusevangeliums aus dem 6. Jahrhundert (Unzial 094), die Flora Graeca Sibthorpiana des englischen Botanikers John Sibthorp, die Landkarte des Rigas Velestinlis; Das Große Wörterbuch der Etymologie, ein historisches byzantinisches Wörterbuch und die ersten Ausgaben von Homers Epen und Gedichten.

Einige weitere Handschriften in dieser Sammlung sind Unzial 075, Unzial 0161 und Minuskel 798.

Weitere Sondersammlungen
Außerdem besitzt die Bibliothek viele Bullen und ein Archiv der Griechischen Revolution.

Weblinks

 Offizielle Website (griechisch)

Einzelnachweise

Museum in Athen
Nationalbibliothek
Bibliothek in Griechenland
Bauwerk in Athen
Theophil von Hansen
Ernst Ziller
Erbaut in den 1900er Jahren
Kulturdenkmal in Athen
Bibliotheksbau
Gegründet 1832

redpajama_set_name: RedPajamaWikipedia


DIG Camp is an innovation camp for middle and high school-aged students. Hosted at the University of South Carolina's Darla Moore School of Business, it exposes students to a week of fun, hands-on projects that stretch their imagination and capabilities. Last year, students created and tested new business ventures. This year, the focus is on innovation in flight. Students will design, build, and fly their own virtual airplanes - then use that knowledge to build a real model in our Grand Flight Challenge.
How do you create new ideas? The world of design thinking.
From identifying opportunities to prototyping - build better.


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The 8700k only has 16 lanes, but yet this build has a M.2? and a 1080ti, will this not limit the performance of the 1080ti?
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Hi, I would have selected 2x16Gb Corsair Vengeance LPX instead of 2x16Gb Corsair Vengeance LED but you only have the LPX available in 4x8Gb, can you make the 2x16Gb LPX option available?


text:
Q: WSUS: Client-Side vs Server-Side Targeting In the WSUS Manual:

Specify how to assign computers to
  computer groups. There are two
  options: server-side targeting and
  client-side targeting. With
  server-side targeting, you manually
  add each computer to its group. With
  client-side targeting, you
  automatically assign the computers by
  using either Group Policy or registry
  keys.

So two that leaves two options, doing server-side in WSUS itself or making a Group Policy (I am going to pretend they didn't even suggest editing the registry on each computer).  What are the benefits / trade offs of the two different methods?

A: Server-side targeting - Easy for small numbers of clients, doesn't require that clients can process group policy (i.e. aren't domain members, typically). Administratively burdensome for large numbers of clients or for clients that change roles and need to have their client group membership dynamically updated. For non-domain-joined clients this is the easiest way to get them into client groups.
Client-side targeting - Requires that clients either be able to process Group Policy (i.e. a member of a domain) or have the settings set in their Local Group Policy or registry (and why you'd do either of those last two things is quite beyond me, as well). Works well if you plan on having client group membership change based on moving the AD object that represents the client between OUs (move from "Staging" to "Production" OUs for new system deployments and want client group membership to change automatically).
I use both at different Customer sites. I find server-side targeting more flexible insofar as making "quick changes" (because I don't have to mess w/ Group Policy and I can see the results of my changes reflected immediately), but client-side handier when I need to the client group membership to reflect some "role" that's implied by the client's location in AD.

A: That greatly depends on what you want to achieve.
Manually assigning computer to groups is very useful when you want to make some tests or limited distribution. I used it many times for initial MSIE or Service Pack deployment.

redpajama_set_name: RedPajamaStackExchange


Just as you must determine the best posting frequency, it is also important to decide what the very best length for your blog postings will be. Of course the length can change, according to your subject matter, but in general your readers will expect you to maintain the approximate length of your blog posts. Most blog posts tend to fall between 250 and 1000 words with the "average" coming in at 500 words.
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For SEO purposes, your blog should be at least 250 words; both extremely long and extremely short web pages are not ranked as highly as those of a more reasonable length. Of course in the end, the content of your blog is much more important than the length, but as an overall SEO strategy, try to keep your blog posts between the prescribed 250 and 1000 words. Your subject matter will also dictate the length in that if you are highlighting a specific product or service, a longer post may be appropriate. If you are responding to a reader's comment or commenting on a newsworthy trend in your industry, a shorter post could work better for your readers and for your SEO.
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The average attention span of a web reader is relatively short; the average length of time a reader will remain on any one blog post is 96 seconds. A mere minute and a half is not much time, so keep this number in mind when determining the best length for your blog post. You will need to communicate the subject matter in that length of time, using short chunks of information with paragraph titles which clearly detail the forthcoming information. If you have been posting for a significant length of time, consider which posts were the most popular. Take a look at your reader feedback in relation to the length and topic of the post. Then take a look at other blogs in your own industry, checking out the average length. These tasks will give you a fairly good idea of what length you need to shoot for when writing your blog.
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This entry was posted in Lawyer Website Copy on January 24, 2014 by James Greenier.


The swap meet will be held at the Will County Fairgrounds, 710 S. West Street in Peotone beginning at 7:00 am. Admission is $10.00 for adults until 10:00 am and then the admission is $9.00 for adults. Vendor spaces are $70.00 for non-motorcycle products and $45.00 for motorcycle spaces. The event will also include food, bands, celebrity appearance, a bike show with trophies awarded and more. For more information call 800-800-6034, email mailto:, or go to http://peotonemotorcycleswap.com/.


text:
UK's CARE2 site Petitions Parliament to Adopt & Tailor UN De-Population Charter
This Forum is Closed > Forum > Health, Family & Eugenics > Eugenics / Depopulation / War On Family (Moderator: HealthWyze) > Topic: UK's CARE2 site Petitions Parliament to Adopt & Tailor UN De-Population Charter
Author Topic: UK's CARE2 site Petitions Parliament to Adopt & Tailor UN De-Population Charter (Read 691 times)
Jonnie Goodboy
The Gulag Archipelago, - had 'Paradise Islands'.
Forwarded this morning in EMAIL format to hundreds of thousands of subscribers, environmentalists, innocent greenies and fairies alike this petition exceeds any of the 'help reduce global famine' or 'save the Brazilian Canopy' that we usually see at CARE2:
Even I signed it, it's that flaming extreme!
"Population Matters for a Healthy Humanity and Planet"
http://www.thepetitionsite.com/takeaction/918/131/704/?z00m=20113546
Human beings have a greater impact on the planet than all other animals combined and, as our population grows, so does the impact on sustainability and the environment.
The UN expects world population to rise from 7 billion today to between 8 and 11 billion by 2050. What we do in the next 10 years will largely determine the scale of this increase and therefore the future quality of human life on the planet and the prospects for survival of our fellow species.
We must do our part. That's why we're asking the Government to adopt a national population policy in order to help stabilise and decrease our numbers to an environmentally sustainable level.
I support Population Matters' call for the government to introduce a policy enabling the UK population to stabilise and then gradually to decrease to an environmentally sustainable level.
[Your comments] So feed on these
And I note, that the next three signatures on the list, are all quite likely from the same person, as two of themn they occur in the same minute with the first one leading by a few seconds. Probably the site admin, or people jealous of my breakdown of the issues. Pathetic, but well ... this proposed depopulation should be fun and clearly all these sub-Utangs need to be gotten rid of somehow, and getting them to sign a petition is just the way for Stealth Government to be able to say: "But it's what you said you wanted".
« Last Edit: November 09, 2011, 05:43:33 am by Jonnie Goodboy » Report Spam Logged
"When the righteous become many, the people rejoice; but when anyone wicked bears rule, the people sigh".
— Prov 29:2
Re: UK's CARE2 site Petitions Parliament to Adopt & Tailor UN De-Population Charter
This Pole of concensus for gullible fools was sponsored by, guess who ...
YES the Optimum Population Trust (who fell out of favour last year after the Alex Jones show exposed their leadership) I mentioned it first on these and the prior forum after I found a sticker on a bus-stop in Scotland. Bad choice of place to put it. What true justification do they have for their beliefs. They are always evolutionary Biologists, who can only by definition see the origins of all life, including humanoid, as a random, per-chance, statistical event involving ridiculously impossible likelihoods of arrangements of amino-acids in protoplasmic soup, and thereofore, also by defintion, pretty easily compare life to a virus. Which is as anyone who follows these events and news breaches, is exactly their MO.
h·t·t·p://populationmatters.org/
"There is something you can do about population growth
Thank you for signing the pledge on the Care2 site calling on the UK government to adopt a national population policy in order to help stabilise and decrease our numbers to an environmentally sustainable level. You clearly recognise that human population size is a factor in the big issues facing humanity. As our patron David Attenborough says, "All environmental problems become harder – and ultimately impossible – to solve with ever more people."
There is one more thing that you can do to help make a difference - support the campaign of Population Matters to raise the issue. Population Matters is the leading population concern group outside the United States. We lobby the government, green campaign groups and other organisations on population issues, appeal to public opinion and carry out research and education into the link between population, the environment and sustainability.
By becoming a member, you will be helping to fund our work. We will keep you informed through our newsletters, magazines and journals and invite you to participate in our activities. A full year's membership only costs ?20 (?5 concessions). Give us a try: you might be pleasantly surprised. You can find out more about us and how to become a member here.
135-137 Station Road
London E4 6AG supporters·@·populationmatters.org
·www.populationmatters.org·
Population Matters is the working name of the Optimum Population Trust. It is a registered charity and a company limited by guarantee registered in England and Wales. Registered charity no. 1114109. Registered company no. 3019081. Registered office as above.
« Last Edit: November 11, 2011, 01:11:45 pm by Jonnie Goodboy » Report Spam Logged
Optimum Pupulation Growth: Here!
http://www.infowars.com/britain-must-set-population-limit-to-safeguard-national-security-say-experts/
'The Optimum Population Trust has written to ministers calling for a policy of 'zero net migration' – matching numbers allowed into Britain each year to numbers leaving.
The UK's population is projected to increase from 60 to 70 million over the next 20 years, and to 85million by 2081.
The trust, a panel of academics and environmentalists, says achieving zero net migration would cut Britain's population in 2081 to 57million.
Mass immigration 'feeds through into rising greenhouse gas emissions' and more congestion, the experts say."

redpajama_set_name: RedPajamaCommonCrawl


Perflurochemicals have been widely used by the textile industry and are as such an organic compound. However certain variations of the compounds proved too large to break down with toxic side effects. 3M's Scotchgard and Du pont's Teflon were both treatments based on this chemistry and both companies took the decision in 2000 to voluntary phase out the specific type of C8 PFOS and PFOA flurocarbons in question.
The environmental impact was deemed serious enough for the EPA to legislate the 2010/2015 PFOA stewardship program, which aims to reduce C8 fluorocarbon chemicals by 100% by 2015. The use of fluorocarbons is still widespread, but these specific compounds, if are not already, continue to be phased out. For these reasons there is a clear drive to move away from fluorocarbon chemistry.


Newly published records for Oregon, Kentucky and Tennessee. In addition, there are newly indexed German Civil registrations and millions of new digital GenealogyBank obituaries.
For these and more free searchable historic records added this week at FamilySearch.org.


Military deminers are clearing mined areas in the Libyan city of Benghazi, where loud blasts from explosives and booby traps have become an all too familiar sound.
Mines planted during more than three years of war in Benghazi are taking a high toll on under-equipped deminers and residents trying to return to districts where protracted battles once took place.
"One of the residents of the building called and asked if one of the mines had exploded in the building and if a woman had passed away, but I told him I hadn't heard about it. When I arrived and asked, they told me it was Mona al-Ebeidy from the first floor",Mohamed Al-Ruwayi a local resident said.
Thank god we have completed some of the work, but some of it has yet to be completed due to a lack of resources, bad circumstances and obstacles.
Military engineers striving to clear the explosives lack mine detectors and are working with basic tools and their bare hands.
"Thank god we have completed some of the work, but some of it has yet to be completed due to a lack of resources, bad circumstances and obstacles",said Engineer Tarek Farkash.
Their task is painstaking and extremely dangerous: 50 have been killed and 60 wounded, according to a military source.
The war in Benghazi erupted in 2014, when Libyan commander Khalifa Haftar began battling Islamists and other opponents, part of a broader conflict that spread in Libya after the fall of Muammar Gaddafi seven years ago.
Haftar's Libyan National Army took a final holdout from its rivals in December, but demining can take months. Souq al-Hout came under the LNA's control early last summer and is still far from being cleared.
Despite warnings from the military and indications of mined areas scribbled on walls, some long-displaced residents impatient to rebuild their lives have gone home, with deadly consequences.
Souq al-Hout resident Mohamed al-Ruwayi, whose building had been cordoned off by the military because of the risk from mines, described how a university teacher had recently returned to visit her home with her husband and was killed by a mine as she was leaving.
Farkash said at least 49 civilians had been killed and 38 injured, with the real number higher as not all cases had been accounted for.
Benghazi's Al Jalaa hospital has been dealing with such casualties since February 2016, when Haftar's forces broke a military deadlock, taking control of the residential district of Laithi. The youngest casualty brought to Al Jalaa was three years old and the oldest 75, a hospital official said.


text:
DINING PROFILE: Serenity Available With Star Of…
The GrunionGrunion News
DINING PROFILE: Serenity Available With Star Of Siam
CALMING FORCE. Star of Siam offers a serene atmosphere for customers to enjoy Thai food.
By The Grunion |
PUBLISHED: November 29, 2013 at 2:00 a.m. | UPDATED: May 25, 2021 at 4:39 p.m.
Many restaurants are extremely noisy these days, but in contrast, Star of Siam offers a calm atmosphere, even when the place is full.
"Some people spend a long time in here and they enjoy the serenity," owner Chef Thaworn Nauklib-Anderson said. There's carpeting, a sound absorbing ceiling and no TV.
After starting on Anaheim Street, they moved to the current Broadway location in 1987 with space for 30. About six years ago, the slot next to them became available, and now Star of Siam can seat at total of 104 people in the two areas.The larger new area is available for private parties.
"It's big enough," Chef Thaworn said, "but not too big. It's kind of friendly, nice and clean."
In Chef Thaworn's words, "We do really good lunch business. We have neighbors and people who come from downtown and we also do a lot of deliveries, both downtown and nearby as well."
Some days, the ratio of take-out and delivery to dine in is 50-50. Sometimes they even make deliveries to staff at downtown restaurants.
Secrets to Success
The secret to the longevity is the same cook and the same owners. They've had many customers from the beginning. They move to Anaheim or San Pedro or go to college but they return to Star of Siam.
"We had one woman who couldn't believe she'd been coming here for 20 years," Chef Thaworn said. "Some customers even call me mom."
Variations on Thai Cuisine
When it first opened, Star of Siam had 60 items on the menu. Today there are more than 100.
"We have a lot of ingredients, including garlic and chili that we use to create many variations," Chef Thaworn said.
Star of Siam features Thai Cuisine, which is divided by geographical area. Isan (which means Northern) features rice, chili sauces, meat, pork and chicken with a touch of salty tastes almost to the exclusion of sweet and sour tastes.
Central Region food is smooth with lasting taste and a touch of sweetness. Food from the south is very hot and includes spiced soup or curry
The most popular dish is the Pad Thai ($8.95), thin rice noodles with shrimp and chicken, egg, bean sprouts and ground peanuts.
For first timers, Chef Thaworn recommends Chicken Satay appetizer, Hot and Sour Soup with shrimp and Chicken Coconut Milk Soup.
"We're able to accommodate diners with special requirements such as allergies, vegetarian diets and we can provide gluten-free dishes," Chef Thaworn said.
Their cocktails are made with Jinro sake and Han Askain Vodka. One of the standouts is Lychee Martini, and according to the menu, "made with Thai Lychee juice, not syrup" and the Blue Raspberry Lemon Drop Martini. "Deep blue like the Gulf of Siam. Tastes good too." Thailand, China, Japan, Holland and the United States are represented in beer choices.
They take orders by phone, by fax and online. And they also offer catering. Luncheon specials are $7.95; dinner combos start at $13.95.
Star of Siam is at 2109 E. Broadway (near Redondo). They're open from 11 a.m. to 10 p.m. Wednesday through Monday. Corkage is $8.
The phone number is 439-1564.
The website is www.starofsimaonline.com. Parking is on the street.
Kurt A. Eichsteadt can be reached at calendar@gazettes.com.
More in The Grunion
Hundreds take to Long Beach streets to tally those who are homeless
City management ends Long Beach Convention Center audit after changes


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Speech Day
Busy A2 Charities Day raises funds for African Vision Malawi
Last weekend, A2 pupils organised and hosted the annual A2 Charities Day.
As in previous years, the Head Boy and Head Girl selected the charity they wished to support, which this year was African Vision Malawi, and specifically their 'A Child is Born' project. The project is devoted to building a Safe Motherhood Unit in Malawi to create a safe and comfortable place for mothers and their new-born babies.
To help focus the fundraising efforts, the Heads of School chose an ambitious target of £20,000 to be raised for the charity. With the target identified, they set about creating a packed programme to entice both parents and pupils and keep them entertained throughout the day.
The day started with an A2 parent drinks reception swiftly followed by lunch, where a mouth-watering menu was served to prepare parents for the afternoon's activities. Shortly after lunch, the silent auction was opened and parents were given the opportunity to bid on luxury items from concert tickets and wine to club memberships and weeklong escapes. All items in the auction were generously donated by parents and local businesses and we would like to thank them for their support. The auction remained open until late in the evening, allowing parents to bid for items and further support the Charities Day.
A fashion show followed, which saw a group of pupils take to the catwalk to showcase their outfits. However, the dog show late in the afternoon was the real highlight, with parents and pupils invited to enter their dog in a range of categories from 'waggiest tail' and 'scruffiest dog' to 'best fancy dress' and 'best trick'. There were a number of great entries on display including one dog dressed as a dinosaur for 'best fancy dress' and an impressive number of tricks from 'high fives' to 'standing on their back legs'.
As the evening drew on parents were invited inside for the final event of the day, the Queen tribute concert. The concert was a lively affair with a number of Queen's biggest hits covered on the Coade Hall stage. While this drew the curtain on a busy day for parents, there were more activities planned for the pupils, who ventured down to the astro pitches for the Bears (boys) v Bees (girls) hockey game, which resulted in a thrilling 0-0 draw before the Bears took the spoils 3-2 on penalty flicks. The day was finally closed by the promises auction in which pupils bid on a selection of items.
Overall the A2 Charities Day was a great success, and we would like to thank all the parents and friends who donated to the silent auction and bid for the lots, supported the weekend's events or simply gave a donation to African Vision Malawi. At the time of writing, over £10,000 had been raised and donations were still coming in.
While it is always difficult to highlight individuals in what was a fine team effort, particular mention must go to the following A2 pupils for their contribution: Lucy W, Tom N, Rose M, Gabby S, Tilly B, Moley C, Eleanor P, Angus P, India G, Hector CM, Issy L and Liam PC.
Finally, a great deal of credit must go to the Heads of School, Poppy T and Rohan E, for their management of the events and their drive and determination in delivering a fantastic weekend for everyone involved, as well as raising a superb sum of money. Well done!
You can still support the A2 Charities Day by donating to African Vision Malawi here and you can also see photos from the day here.
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