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  • Economic Segregation In New York City Schools

    by Kinga Wysienska-Di Carlo & Matthew Di Carlo on September 28, 2016

    Although student segregation by race and ethnicity is well documented in U.S. public schools, the body of evidence on the related outcome of economic school segregation (e.g., by income) is considerably smaller (Reardon and Owens 2014).

    In general, economic segregation of students is increasing nationally over the past few decades, both between districts and between schools (Owens et al. 2014). It is inevitable that these aggregate trends vary widely by state, metropolitan area, and district. We were curious as to the situation in New York City, the nation’s largest district, but were unable to find any NYC-specific results, particularly results that included different types of segregation measures.

    We therefore decided to take a quick look ourselves, using data from the NYC Department of Education. The very brief analysis below uses eligibility for subsidized lunch (free and reduced-price lunch, or FRL) as a (very) rough income proxy, and segregation is measured between district schools only (charters are not included) from 2002 to 2015. In the graph below, we characterize within-district, between-school segregation using two different and very common approaches, exposure and dissimilarity.

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  • The Details Matter In Teacher Evaluations

    by Matthew Di Carlo on September 22, 2016

    Throughout the process of reforming teacher evaluation systems over the past 5-10 years, perhaps the most contentious, discussed issue was the importance, or weights, assigned to different components. Specifically, there was a great deal of debate about the proper weight to assign to test-based teacher productivity measures, such estimates from value-added and other growth models.

    Some commentators, particularly those more enthusiastic about test-based accountability, argued that the new teacher evaluations somehow were not meaningful unless value-added or growth model estimates constituted a substantial proportion of teachers’ final evaluation ratings. Skeptics of test-based accountability, on the other hand, tended toward a rather different viewpoint – that test-based teacher performance measures should play little or no role in the new evaluation systems. Moreover, virtually all of the discussion of these systems’ results, once they were finally implemented, focused on the distribution of final ratings, particularly the proportions of teachers rated “ineffective.”

    A recent working paper by Matthew Steinberg and Matthew Kraft directly addresses and informs this debate. Their very straightforward analysis shows just how consequential these weighting decisions, as well as choices of where to set the cutpoints for final rating categories (e.g., how many points does a teacher need to be given an “effective” versus “ineffective” rating), are for the distribution of final ratings.

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  • An Alternative Income Measure Using Administrative Education Data

    by Matthew Di Carlo on September 16, 2016

    The relationship between family background and educational outcomes is well documented and the topic, rightfully, of endless debate and discussion. A students’ background is most often measured in terms of family income (even though it is actually the factors associated with income, such as health, early childhood education, etc., that are the direct causal agents).

    Most education analyses rely on a single income/poverty indicator – i.e., whether or not students are eligible for federally-subsidized lunch (free/reduced-price lunch, or FRL). For instance, income-based achievement gaps are calculated by comparing test scores between students who are eligible for FRL and those who are not, while multivariate models almost always use FRL eligibility as a control variable. Similarly, schools and districts with relatively high FRL eligibility rates are characterized as “high poverty.” The primary advantages of FRL status are that it is simple and collected by virtually every school district in the nation (collecting actual income would not be feasible). Yet it is also a notoriously crude and noisy indicator. In addition to the fact that FRL eligibility is often called “poverty” even though the cutoff is by design 85 percent higher than the federal poverty line, FRL rates, like proficiency rates, mask a great deal of heterogeneity. Families of two students who are FRL eligible can have quite different incomes, as could two families of students who are not eligible. As a result, FRL-based estimates such as achievement gaps might differ quite a bit from those calculated using actual family income from surveys.

    A new working paper by Michigan researchers Katherine Michelmore and Susan Dynarski presents a very clever means of obtaining a more accurate income/poverty proxy using the same administrative data that states and districts have been collecting for years.

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  • Contingent Faculty At U.S. Colleges And Universities

    by Matthew Di Carlo on September 9, 2016

    In a previous post, we discussed the prevalence of and trends in alternative employment arrangements, sometimes called “contingent work,” in the U.S. labor market. Contingent work is jobs with employment arrangements other than the “traditional” full-time model, including workers with temporary contracts, independent contractors, day laborers, and part-time employees.

    Depending on how one defines this group of workers, who are a diverse group but tend to enjoy less job stability and lower compensation, they comprise anywhere between 10 and 40 percent of the U.S. workforce, and this share increased moderately between 2000 and 2010. Of course, how many contingents there are, and how this has changed over time, varies quite drastically by industry, as well as by occupation. For example, in 1990, around 28 percent of staffing services employees (sometimes called “temps”) worked in blue collar positions, while 42 percent had office jobs. By 2009, these proportions had reversed, with 41 percent of temps in blue collar jobs and 23 percent doing office work. This is a pretty striking change.

    Another industry/occupation in which there has been significant short term change in the contingent work share is among faculty and instructors in higher education institutions.

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  • Economic Shocks And Attitudes Toward Redistribution

    by Kinga Wysienska-Di Carlo & Matthew Di Carlo on September 2, 2016

    In the wake of the financial crisis that began in 2007, as well as the subsequent recession, there has been a great deal of attention paid to income inequality. Specifically, there was a pervasive argument among many Americans that the discrepancies in income between the top and bottom are too large, and that the fruits of economic growth are predominantly going to the highest earners (the so-called “one percent”).

    Among those who believe that income inequality is too high, the solutions might include policies such as more progressive taxation, stronger regulation, and more generous policies to help lower income families. That is, they might generally support some increased role for government in addressing this issue. Insofar as individuals’ attitudes tend to respond to changes in their own circumstances (e.g., Owens and Pedulla 2013), as well as to overall economic conditions, one would possibly expect an increase in support for government efforts to reduce inequality during and after the financial crisis.

    We might take a look at this proposition using a General Social Survey (GSS) question asking respondents to characterize their support (on a scale of 1-7) for the statement that the government should reduce income differences between the rich and poor. The graph below presents the average value of this scale between 1986 and 2014. Note that higher values in the graph represent greater support for government action.

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  • Perceived Job Security Among Full Time U.S. Workers

    by Matthew Di Carlo on August 18, 2016

    In a previous post, we discussed some recent data on contingent work or alternative employment relationships – those that are different from standard full time jobs, including temporary help, day labor, independent contracting, and part time jobs. The prevalence of and trends in contingent work vary widely depending on which types of arrangements one includes in the definition, but most of them are characterized by less security (and inferior wages and benefits) relative to “traditional” full time employment.

    The rise of contingent work is often presented as a sign of deteriorating conditions for workers (see the post mentioned above for more discussion of this claim). Needless to say, however, unemployment insecurity characterizes many jobs with "traditional" arrangements -- sometimes called precarious work -- which of course implies that contingent work is an incomplete conceptualization of the lack of stability that is its core feature.

    One interesting way to examine job security is in terms of workers’ views of their own employment situations. In other words, how many workers perceive their jobs as insecure, and how has this changed over time? Perceived job security not only serves as a highly incomplete and imperfect indicator of “real” job security, but it also affects several meaningful non-employment outcomes related to well being, including health (e.g., Burgard et al. 2009). We might take a very quick look at perceived job security using data from the General Social Survey (GSS) between 1977 and 2014.

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  • On Focus Groups, Elections, and Predictions

    by Kinga Wysienska-Di Carlo on August 11, 2016

    Focus groups, a method in which small groups of subjects are questioned by researchers, are widely used in politics, marketing, and other areas. In education policy, focus groups, particularly those comprised of teachers or administrators, are often used to design or shape policy. And, of course, during national election cycles, they are particularly widespread, and there are even television networks that broadcast focus groups as a way to gauge the public’s reaction to debates or other events.

    There are good reasons for using focus groups. Analyzing surveys can provide information regarding declaratory behaviors and issues’ rankings at a given point in time, and correlations between these declarations and certain demographic and social variables of interest. Focus groups, on the other hand, can help map out the issues important to voters (which can inform survey question design), as well investigate what reactions certain presentations (verbal or symbolic) evoke (which can, for example, help frame messages in political or informational campaigns).

    Both polling/surveys and focus groups provide insights that the other method alone could not. Neither of them, however, can answer questions about why certain patterns occur or how likely they are to occur in the future. That said, having heard some of the commentary about focus groups, and particularly having seen them being broadcast live and discussed on cable news stations, I feel strongly compelled to comment, as I do whenever data are used improperly or methodologies are misinterpreted.

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  • Thinking About Tests While Rethinking Test-Based Accountability

    by Matthew Di Carlo on August 5, 2016

    Earlier this week, per the late summer ritual, New York State released its testing results for the 2015-2016 school year. New York City (NYC), always the most closely watched set of results in the state, showed a 7.6 percentage point increase in its ELA proficiency rate, along with a 1.2 percentage point increase in its math rate. These increases were roughly equivalent to the statewide changes.

    City officials were quick to pounce on the results, which were called “historic,” and “pure hard evidence” that the city’s new education policies are working. This interpretation, while standard in the U.S. education debate, is, of course, inappropriate for many reasons, all of which we’ve discussed here countless times and will not detail again (see here). Suffice it to say that even under the best of circumstances these changes in proficiency rates are only very tentative evidence that students improved their performance over time, to say nothing of whether that improvement was due to a specific policy or set of policies.

    Still, the results represent good news. A larger proportion of NYC students are scoring proficient in math and ELA than did last year. Real improvement is slow and sustained, and this is improvement. In addition, the proficiency rate in NYC is now on par with the statewide rate, which is unprecedented. There are, however, a couple of additional issues with these results that are worth discussing quickly.

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  • A Small But Meaningful Change In Florida's School Grades System

    by Matthew Di Carlo on July 28, 2016

    Beginning in the late 1990s, Florida became one of the first states to assign performance ratings to public schools. The purpose of these ratings, which are in the form of A-F grades, is to communicate to the public “how schools are performing relative to state standards.” For elementary and middle schools, the grades are based entirely on standardized testing results.

    We have written extensively here about Florida’s school grading system (see here for just one example), and have used it to illustrate features that can be found in most other states’ school ratings. The primary issue is the heavy reliance that states place on how highly students score on tests, which tells you more about the students the schools serve than about how well they serve those students – i.e., it conflates school and student performance. Put simply, some schools exhibit lower absolute testing performance levels than do other schools, largely because their students enter performing at lower levels. As a result, schools in poorer neighborhoods tend to receive lower grades, even though many of these schools are very successful in helping their students make fast progress during their few short years of attendance.

    Although virtually every states’ school rating system has this same basic structure to varying degrees, Florida’s system warrants special attention, as it was one of the first in the nation and has been widely touted and copied (as well as researched -- see our policy brief for a review of this evidence). It is also noteworthy because it contains a couple of interesting features, one of which exacerbates the aforementioned conflation of student and school performance in a largely unnoticed manner. But, this feature, discussed below, has just been changed by the Florida Department of Education (FLDOE). This correction merits discussion, as it may be a sign of improvement in how policymakers think about these systems.

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  • A Myth Grows In The Garden State

    by Matthew Di Carlo on July 15, 2016

    New Jersey Governor Chris Christie’s recently announced a new "fairness funding" plan to provide every school district in his state roughly the same amount of per-pupil state funding. This would represent a huge change from the current system, in which more state funds are allocated to the districts that serve a larger proportion of economically disadvantaged students. Thus, the Christie proposal would result in an increase in state funding for middle class and affluent districts, and a substantial decrease in money for poorer districts. According to the Governor, the change would reduce the property tax burden on many districts by replacing some of their revenue with state money.

    This is a very bad idea. For one thing, NJ state funding of education is already about 7-8 percent lower than it was in 2008 (Leachman et al. 2015). And this plan would, most likely, cut revenue in the state’s poorest districts by dramatic amounts, absent an implausible increase in property tax rates. It is perfectly reasonable to have a discussion about how education money is spent and allocated, and/or about tax structure. But it is difficult to grasp how serious people could actually conceive of this particular idea. And it’s actually a perfect example of how dangerous it is when huge complicated bodies of empirical evidence are boiled down to talking points (and this happens on all “sides” of the education debate).

    Pu simply, Governor Christie believes that “money doesn’t matter” in education. He and his advisors have been told that how much you spend on schools has little real impact on results. This is also a talking point that, in many respects, coincides with an ideological framework of skepticism toward government and government spending, which Christie shares.

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