Interaction Effects of Socioeconomic Status on Emerging Literacy and Literacy Skills among Pre-Kindergarten and Kindergarten Children: A Comparison Study

Socioeconomic differences in children’s reading and educational outcomes have been thoroughly documented throughout literature. Bobalik, Scarber, and Toon (2017) examined the link between socioeconomic status (SES) and classroom instruction on emerging literacy skills in pre-kindergarten children. The results supported the theory that children identified as belonging to a low socioeconomic status enter school with lower emerging literacy skills and benefit most from academic instruction; these children’s literacy skills substantially increased throughout the academic year, growing closer to those of their peers who were identified with a high socioeconomic status. The aim of the present study was to expand our understanding of the interaction effects of socioeconomic status and curriculum on emerging literacy and literacy skills by continuing the research into kindergarten. This study examined whether 1) differences in groups continued to grow closer to the mean or 2) the differences in groups became greater with the introduction of reading skills in kindergarten. Children (N=33) were recruited from a private school and a public school. The children from the public school who qualified for the Federal Poverty Guidelines for free/reduced lunch were assigned as having a low socioeconomic status, and children from the private school were assigned as having a high socioeconomic status. The Phonological Awareness Literacy Screening – K (PALS-K) was used to measure the literacy skills in the kindergarten children. Results of the study indicated that literacy scores between the socioeconomic groups were not significantly different at the kindergarten level, however differences between the mean scores of the pre-kindergarten and kindergarten groups were found to be significant

Impacts of the Administration's 2007 Farm Bill Proposal on Representative Crops, Dairy and Beef Cattle Farms -- Revised

For the first time in two decades, the Secretary of Agriculture provided the House and Senate Agriculture Committees a farm bill proposal from the Administration. The Administration’s Proposal is a comprehensive revision of the 2002 farm bill with suggested changes to all titles. Four major proposed changes to Title 1 Commodity Programs are analyzed and reported in this Briefing Paper. The four key policy changes analyzed are: - an increase in direct payment rates, - a reduction in loan rates for most crops, - the replacement of the counter cyclical payment (CCP) program with a counter cyclical revenue (CCR) program, and - a change in eligibility for farm program payments by using $200,000 adjusted gross income (AGI) for a means test. The economic impact of the Administration’s Proposal on the viability of 99 representative crop, dairy, and beef cattle farms is compared to a base situation of continuing the current farm bill through 2012. This report is a companion to FAPRI-UMC Report #11-07 that contains sector level impacts.Agribusiness, Agricultural and Food Policy, Crop Production/Industries, Livestock Production/Industries,

The Farm Level Economic Impacts of Increased Cash Lease Rates

Higher commodity price expectations have led to increases in cash lease rates nationwide. This study evaluates the farm level impacts of higher cash lease rates. Current levels of cash rents along with land tenure arrangements of specific farms are instrumental in determining the impacts of increases in lease rates.Farm Management, Land Economics/Use,

Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tGraph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz) and low-alpha (6-9 Hz) bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics.Funding was from Epilepsy Research UK (http://www.epilepsyresearch.org.uk) via grant number A1007 and the Medical Research Council (http://www.mrc.ac.uk) via grants (MR/K013998/1 and G0701310)

A critical role for network structure in seizure onset: a computational modeling approach

Published onlineJournal ArticleRecent clinical work has implicated network structure as critically important in the initiation of seizures in people with idiopathic generalized epilepsies. In line with this idea, functional networks derived from the electroencephalogram (EEG) at rest have been shown to be significantly different in people with generalized epilepsy compared to controls. In particular, the mean node degree of networks from the epilepsy cohort was found to be statistically significantly higher than those of controls. However, the mechanisms by which these network differences can support recurrent transitions into seizures remain unclear. In this study, we use a computational model of the transition into seizure dynamics to explore the dynamic consequences of these differences in functional networks. We demonstrate that networks with higher mean node degree are more prone to generating seizure dynamics in the model and therefore suggest a mechanism by which increased mean node degree of brain networks can cause heightened ictogenicity.Medical Research Counci

AN INTERACTIVE ILLUSTRATION OF FARM PROGRAM PROVISIONS

Explaining the details and the impacts of government program provisions to agricultural producers can be a challenge for extension educators. This paper introduces a visual interactive tool that demonstrates the calculations of government payments established in the 2002 farm bill. Additionally, the paper explains how the tool is created in Microsoft® Excel and may be used in other areas.Agricultural and Food Policy,

Utilization of soil organic phosphorus as a strategic approach for sustainable agriculture

Soil organic phosphorus (P org ) can significantly assist in minimizing the adverse effects of chemi- cal phosphorus fertilizers on aquatic and marine resources. Success to achieve the desired last- ing transformation is primarily reliant on the drastic reduction of wasteful applications of chemical phosphorus fertilizers, thereby paving the way for proper investment of soil P org reserves. To this end, organically-bound phosphorus can be viewed as a cornerstone for the future development of agriculture. Thus, we consider it very timely to emphasize the suitability of soil P org to lead the way

Emergence of a Norm from Resistance: Using Simulation to Explore the Macro Implications of Social Identity Theory

We usually hope that social norms discourage injustice. However, we are all witnesses to harmful norms enforced by governments, such as xenophobia, which need to be contested and changed. Previous studies have concluded that it is possible to change a harmful norm through contestation by powerless actors if suitable structural conditions exist. However, these structural conditions have not been sufficiently studied and, as such, are the focus of this paper. Our paper begins with a review of well-established micro-level theories of social identity theory (SIT), recast as a set of 42 discrete theoretical statements. These statements are then re-expressed in the form of a systems-level theory of macro-changes in societal norms using the system dynamics approach. The over-time dynamic behavior simulated using this structure is compared to events in two well-known case studies of changes in societal norms: women’s suffrage between 1830 and 1920, and the emergence of more tolerant lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) norms in the US between 1950 and 2018. Further simulations of the model explore the roles of anger and social outrage, foreshadowing the ability of simulation-based experiments, such as the one presented here, to explore in a robust way a wide range of (undemocratic) regimes under counter-factual conditions