Impacts of the Teach For America Investing in Innovation Scale-Up

In 2010, Teach For America (TFA) launched a major expansion effort, funded in part by a five-year Investing in Innovation (i3) scale-up grant of $50 million from the U.S. Department of Education. Using a rigorous random assignment design to examine the effectiveness of TFA elementary school teachers in the second year of the i3 scale-up, Mathematica Policy Research found that first- and second-year corps members recruited and trained during the scale-up were as effective as other teachers in the same high-poverty schools in both reading and math. To estimate the effectiveness of TFA teachers relative to the comparison teachers, we compared end-of-year test scores of students assigned to the TFA teachers and those assigned to the comparison teachers. Because students in the study were randomly assigned to teachers, we can attribute systematic differences in achievement at the end of the study school year to the relative effectiveness of TFA and comparison teachers, rather than to the types of students taught by these two different groups of teachers. In addition to the impact analysis described in this report, the evaluation included an implementation analysis that describes key features of TFA's program model and its implementation of the i3 scale-up

Strategic tradeoffs in competitor dynamics on adaptive networks

Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.Comment: 20 pages (11 pages for the main text and 9 pages of supplementary material

Geometry shapes evolution of early multicellularity

Organisms have increased in complexity through a series of major evolutionary transitions, in which formerly autonomous entities become parts of a novel higher-level entity. One intriguing feature of the higher-level entity after some major transitions is a division of reproductive labor among its lower-level units. Although it can have clear benefits once established, it is unknown how such reproductive division of labor originates. We consider a recent evolution experiment on the yeast Saccharomyces cerevisiae as a unique platform to address the issue of reproductive differentiation during an evolutionary transition in individuality. In the experiment, independent yeast lineages evolved a multicellular "snowflake-like'' cluster form in response to gravity selection. Shortly after the evolution of clusters, the yeast evolved higher rates of cell death. While cell death enables clusters to split apart and form new groups, it also reduces their performance in the face of gravity selection. To understand the selective value of increased cell death, we create a mathematical model of the cellular arrangement within snowflake yeast clusters. The model reveals that the mechanism of cell death and the geometry of the snowflake interact in complex, evolutionarily important ways. We find that the organization of snowflake yeast imposes powerful limitations on the available space for new cell growth. By dying more frequently, cells in clusters avoid encountering space limitations, and, paradoxically, reach higher numbers. In addition, selection for particular group sizes can explain the increased rate of apoptosis both in terms of total cell number and total numbers of collectives. Thus, by considering the geometry of a primitive multicellular organism we can gain insight into the initial emergence of reproductive division of labor during an evolutionary transition in individuality.Comment: 7 figure

Assessing the Effectiveness of Teach For America's Investing in Innovation Scale-Up

In 2010, TFA launched a major expansion effort, funded in part by a five-year Investing in Innovation (i3) scale-up grant of $50 million from the U.S. Department of Education. By the 2012 -- 2013 school year -- the second year of the scale-up -- TFA had expanded its placements of first- and second-year corps members by 25 percent. This study examines the effectiveness of TFA elementary school teachers hired during the first two years of the i3 scale-up, relative to other teachers in the same grades and school

NMR Resonance Assignment of the Therapeutic RNA Aptamer Macugen in Complex with its in Vivo Target, the Heparin Binding Domain of VEGF165

Aptamers consist of nucleic acids that are selected from an in vitro library in order to bind a specific target or catalyze a reaction. Many aptamer-ligand structures have been solved in recent years to characterize the molecular mechanisms that explain the high affinity and specificity observed in these interactions. To this end, NMR resonance assignment experiments were performed as a necessary first step to calculating the solution structure of a therapeutically-active RNA aptamer, Macugen, bound to its in vivo target, the heparin binding domain (HBD) of vascular endothelial growth factor 165 (VEGF165). Though the resonance assignment of Macugen is challenging due to its inability to be isotopically-labeled, techniques were employed that take advantage of the unique chemical modifications of this nucleic acid that are not present in traditional, unmodified RNA. Using the information obtained from two-dimensional heteronuclear (19F, 1H) and homonuclear (1H, 1H) experiments, assignments were made for a sizable number of Macugen atoms. The assignments made in this work will be necessary to calculate a solution structure to better understand the molecular mechanisms that give rise to the high affinity and specificity observed in the Macugen-HBD complex