Once A Felon….Always A Felon? A Comparative Case Study Of The Experiences Of Convicted African-American Fathers

Currently, African-Americans account for 12.3% of the U.S. population but represent 38% of the prison population (The Sentencing Project, 2016). Of the many African-American males sent to prison each year, there is limited research that explores the impact a conviction has on African-American fathers. Within the literature, researchers (Laakso & Nygaard, 2012; Miller, et. al., 2013, Flouri & Buchanan, 2002; Lee, Sansone, Swanson, & Tatum, 2012; Johnson & Easterling, 2015; Miller, 2006; Lopez & Bhat, 2007; Aaron & Dallaire, 2009) only focus on the effect incarceration has on children and the experiences of fathers while incarcerated (Roy & Dyson, 2005; Turner & Peck, 2002; Landreth & Lobaugh, 1998; Tripp, 2001; Arditti, Smock, & Parkman, 2005; Lange, 2001). The goal of this study are to (a) explore the experiences of convicted African-American fathers since their reentry into society, (b) in sharing their experiences, examined how convicted African-Americans fathers described the relationship with their children, and (c) compared the overall experiences of the convicted African-American fathers for similarities or differences since their reentry into society. The study took place while the fathers were clients at the Midlands Fatherhood Coalition located in Columbia, South Carolina. Using Bronfenbrenner’s Ecological Systems Theory (1977) as the framework, the study explored the barriers convicted African-American fathers face within the different systems they live in every day. Results showed the fathers experienced difficulty finding sustainable employment and reestablishing a parental role with their children due to their conviction and incarceratio

Fitting Linear Mixed-Effects Models using lme4

Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.Comment: 51 pages, including R code, and an appendi

911: The Call That No One Answered

Across the country, municipalities are updating their public service agencies with the addition of advanced 911 emergency telephone systems

Individual Article Purchase: Catching the Wave of the Future, Or Getting Pounded on the Reef

For many libraries, particularly small to midsize academic libraries, journals have placed significant strains on the acquisitions budget. For fiscal year 2012–2013 the Volpe Library at Tennessee Tech University faced a significant materials budget shortfall. Rather than simply cutting titles to cover the shortfall or asking the administration for more money, we concluded that the existing system of acquiring and delivering information packaged in journals was not sustainable for us. Therefore, we embarked on a yearlong process to develop a different way of providing article information that would more efficiently use the budget that we have. The process we have developed focuses more heavily on purchasing individual articles, using the Copyright Clearance Center (CCC) product Get it Now, in an attempt to maximize the impact of our budget resources. This paper describes the issues prompting the change and the process that was used to prepare a plan to meet the budget challenge. It also includes a description of the final plan, the implementation of the plan and early results that are available on the operation of the new process

Estimating the Multilevel Rasch Model: With the lme4 Package

Traditional Rasch estimation of the item and student parameters via marginal maximum likelihood, joint maximum likelihood or conditional maximum likelihood, assume individuals in clustered settings are uncorrelated and items within a test that share a grouping structure are also uncorrelated. These assumptions are often violated, particularly in educational testing situations, in which students are grouped into classrooms and many test items share a common grouping structure, such as a content strand or a reading passage. Consequently, one possible approach is to explicitly recognize the clustered nature of the data and directly incorporate random effects to account for the various dependencies. This article demonstrates how the multilevel Rasch model can be estimated using the functions in R for mixed-effects models with crossed or partially crossed random effects. We demonstrate how to model the following hierarchical data structures: a) individuals clustered in similar settings (e.g., classrooms, schools), b) items nested within a particular group (such as a content strand or a reading passage), and c) how to estimate a teacher x content strand interaction.