Our study examined the relation of advanced math course-taking to the educational attainment of rural youth. We used data from the Educational Longitudinal Study of 2002. Regression analyses demonstrated that when previous math achievement was accounted for rural students take advanced math at a significantly lower rate than urban students. Compared to urban students, rural students have less change in their math achievement from 10th to 12th grade, are less likely to be enrolled in a 4-year college two years postsecondary, and these differences are explained by advanced math course-taking. Limitations, implications, and future research directions are discussed.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586243PMC

Publication Analysis

Top Keywords

advanced math
16
educational attainment
8
attainment rural
8
rural youth
8
math course-taking
8
math achievement
8
rural students
8
urban students
8
math
6
relation opportunity
4

Similar Publications

Aging in a weighted ensemble of excitable and self-oscillatory neurons: The role of pairwise and higher-order interactions.

Chaos

January 2025

International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Bunkyo Ku, Tokyo 113 8654, Japan.

We investigate the aging transition in networks of excitable and self-oscillatory units as the fraction of inherently excitable units increases. Two network topologies are considered: a scale-free network with weighted pairwise interactions and a two-dimensional simplicial complex with weighted scale-free pairwise and triadic interactions. Without triadic interactions, the aging transition from collective oscillations to oscillation death (inhomogeneous stationary states) can occur either suddenly or through an intermediate state of partial oscillation.

View Article and Find Full Text PDF

BACT: nonparametric Bayesian cell typing for single-cell spatial transcriptomics data.

Brief Bioinform

November 2024

Institute of Statistics and Big Data, Renmin University of China, No. 59 Zhongguancun Street, 100872 Beijing, China.

The spatial transcriptomics is a rapidly evolving biological technology that simultaneously measures the gene expression profiles and the spatial locations of spots. With progressive advances, current spatial transcriptomic techniques can achieve the cellular or even the subcellular resolution, making it possible to explore the fine-grained spatial pattern of cell types within one tissue section. However, most existing cell spatial clustering methods require a correct specification of the cell type number, which is hard to determine in the practical exploratory data analysis.

View Article and Find Full Text PDF

New reverse sum Revan indices for physicochemical and pharmacokinetic properties of anti-filovirus drugs.

Front Chem

December 2024

Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai, Tamil Nadu, India.

Ebola and Marburg viruses, biosafety level 4 pathogens, cause severe hemorrhaging and organ failure with high mortality. Although some FDA-approved vaccines or therapeutics like Ervebo for Zaire Ebola virus exist, still there is a lack of effective therapeutics that cover all filoviruses, including both Ebola and Marburg viruses. Therefore, some anti-filovirus drugs such as Pinocembrin, Favipiravir, Remdesivir and others are used to manage infections.

View Article and Find Full Text PDF

The study has investigated the implications of three estimation methods, namely L-moments, Maximum Likelihood, and Maximum Product of Spacing (MPS), for fitting the four-parameter Kappa Distribution (KAPD) in extreme value analysis using Monte Carlo simulations. The accuracy of the estimates has been evaluated using root mean square error (RMSE) and bias. The paper also includes an analysis of the effect of the estimation method on the estimated quantiles considering a real-life example of annual maximum peak flows and the Generalized Normal Distribution as the error distribution.

View Article and Find Full Text PDF

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.

Nat Commun

January 2025

University/BHF Centre for Cardiovascular Science, University of Edinburgh, The Queen's Medical Research Institute, Edinburgh BioQuarter, 47 Little France Crescent, Edinburgh, UK.

Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, we use deep learning to measure bone marrow adiposity in the femoral head, total hip, femoral diaphysis, and spine from MRI scans of approximately 47,000 UK Biobank participants, including over 41,000 white and over 6300 non-white participants.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!