Today, All Children: Can Teach for America Bridge the Achievement Gap?

Since Teach for America\u27s founding in 1989, it has weathered a number of criticisms: could young, well-intentioned corps members unknowingly harm children by virtue of a lack of experience in teaching and unfamiliarity with poverty-stricken, primarily Black and Latino communities? Would a two year time commitment destabilize the already unpredictable lives of poor children? Can a program recruit good teachers, even if it does not require rigorous training or experience with children? And will more educational advocates solve the seemingly intractable problems of low-income schools, if those that already exist have failed thus far? I aim to examine TFA’s model in light of these critiques, using evidence from existing educational research to determine what effect, if any, TFA teachers have on their students. My focus will be on the children that TFA seeks to serve; if I were a student in an inner-city school, would I be better or worse off with a TFA teacher? If I sent my child to a poverty-stricken rural school, would I want a TFA corps member at the head of his/her classroom

Henri Temianka Correspondence; (steinway)

https://digitalcommons.chapman.edu/temianka_correspondence/2883/thumbnail.jp

SKELETONS IN THE DATABASE: AN EARLY ANALYSIS OF THE CFPB\u27S CONSUMER COMPLAINTS

Analyzing a new dataset of 110,000 consumer complaints lodged with the Consumer Financial Protection Bureau (the CFPB or the Bureau ), the authors find that: (i) Bank of America, Citibank, and PNC Bank were significantly less timely in responding to consumer complaints than the average financial institution; (ii) consumers of some of the largest financial services providers, including Wells Fargo, American Express ( Amex ), and Bank of America, were significantly more likely than the average consumer to dispute the provider\u27s response to their initial complaints; and (iii) among the companies included in the database that provide mortgages, OneWest Bank, HSBC, Nationstar Mortgage, and Bank of America all received more mortgage complaints relative to mortgages sold than other mortgage providers. In addition, regression analysis suggests that consumer financial companies respond differently to complaints, depending on the type of product and issues involved, thereby generating significant differences in the timeliness of responses and whether consumers dispute those responses. Moreover, demographics matter: mortgage complaints per mortgage significantly increased in ZIP codes with larger proportions of certain populations, including Blacks and Hispanics. Companies were also less timely, and more likely to have their responses disputed, in areas with higher concentrations of senior citizens and college students, groups on which the CFPB is mandated to focus

The Crisis Close at Hand: How COVID-19 Challenges Long-Term Care Planning for Adults with Intellectual Disability

© 2020 Charmaine Wright et al. Published by Mary Ann Liebert, Inc. Whether cared for in the community or in a facility, adults with intellectual disability are among the most vulnerable individuals in the United States. Families caring for these individuals face financial, social, and emotional stress as they navigate long-term care choices for their loved ones. COVID-19 has stressed an already overwhelmed and disparate system

JCoDA: a tool for detecting evolutionary selection

<p>Abstract</p> <p>Background</p> <p>The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences.</p> <p>Results</p> <p>JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway.</p> <p>Conclusions</p> <p>JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at <url>http://www.tcnj.edu/~nayaklab/jcoda</url>.</p

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions