Effectiveness of manual gesture treatment on residual /r/ articulation errors

The functional speech sound disorder, American English /r/ articulation errors, presents a unique and confounding clinical challenge as therapy resistant residual errors persist into adolescence and adulthood in many cases. Finding paucity of empirical research for /r/ treatment, evidence-based practice (EBP) exploration in motor-related disorders informed clinical practice and research directions. This study investigated the efficacy of manual mimicry (a kinesthetic, gestural, and visual cue) in treating intractable /r/ errors in a young adult using a single subject ABAB design. Perceptual accuracy judgments of three types of listeners (experts, graduate clinician, and naïve listeners) indicated a positive treatment effect of manual mimicry cueing on vocalic /r/ sound productions. Electropalatograpy (EPG) outcome measures showed limited ability to accurately reflect perceptual changes quantitatively. These findings from an exploratory study provide initial evidence that perceptual saliency of /r/ productions may be potentially remediated using a kinesthetic, gestural, and visual cue during treatment

The Changing Motivations of First-Generation College Students

Past research has clearly indicated that first-generation college students are a unique cohort facing specific obstacles on their journey through higher education. That said, it is crucial to understand their motivations for pursuing a college degree in order to better help guide them throughout their studies. Furthermore, comparing these motivations and motivation changes to those of continuing-generation college students provides further insight regarding the uniqueness of first-generation college students. In Study 1, we studied this by asking students to recall their past motivations for enrolling in college and cite their present reasons for being in college. In Study 2, we studied the same motivations, but in a longitudinal format over the course of one college semester. The results of both Study 1 and Study 2 indicated that overall, the motivations of first-generation college students do not change much over time and are not very different from those of continuing-generation college students. Understanding this information is crucial is helping to integrate the two groups as well as providing a more positive higher education experience for first-generation students

Using Samples of Unequal Length in Generalized Method of Moments Estimation

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent estimators that are consistent, asymptotically normal, and more efficient asymptotically than standard GMM. We apply these methods to estimating predictive regressions in international data and show that the use of the full sample affects point estimates and standard errors for both assets with data available for the full period and assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones. These methods are extended to more general patterns of missing data, and are shown to be more efficient than estimators that ignore intervals of the data, and thus more efficient than standard GMM

Using Samples of Unequal Length in Generalized Method of Moments Estimation

Many applications in financial economics use data series with different starting or ending dates. This paper describes an estimation method, based on the generalized method of moments (GMM), which makes use of all available data for each moment condition. We introduce two asymptotically equivalent estimators that are consistent, symptotically normal, and more efficient asymptotically than standard GMM. We illustrate these estimators in an application to mutual fund performance evaluation. Both estimators are extended to general patterns of missing data, and shown to be more efficient than estimators that ignore intervals of the data, and thus more efficient than standard GMM

Using Samples of Unequal Length in Generalized Method of Moments Estimation

This paper describes estimation methods, based on the generalized method of moments (GMM), applicable in settings where time series have different starting or ending dates. We introduce two estimators that are more efficient asymptotically than standard GMM. We apply these to estimating predictive regressions in international data and show that the use of the full sample affects inference for assets with data available over the full period as well as for assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones

Discussing Difficult Topics—Drawing on Circles (and the Philosophy of Circles)

One key concern of Mellon faculty is how to facilitate discussions on difficult topics, such as racism and other forms of oppression. The Circles training in fall semester 2016 was one initiative Mellon funds have sponsored to provide faculty with tools to address this concern. Circle work was already a part of our campuses. Circles of Understanding hosted by International and Intercultural Student Services and courses in mediation and restorative justice taught through Communication and Peace Studies are two examples. The fall training sought to build on this foundation (as well as to respond to faculty interest in circles). Our project comes out of this ongoing conversation and seeks further inroads to transformative practices. The portion of our project included here defines what Circles are and shares two perspectives about the use of Circles as a means of practicing inclusive discussion with students, particularly about more fraught or challenging subject matters. Our project aims specifically to reflect on ways in which Circles, and the philosophy of Circles, might provide new approaches to learning, as well as to restorative work in our campus community. Accordingly, our introduction addresses the question: what are Circles and how do they work? The subsequent contributions from Julie Lynch, Brandyn Woodard, and Jessica Harkins begin to explore how circles can relate to inclusivity in the classroom and in our community

Does Mutual Fund Performance Vary over the Business Cycle?

Conditional factor models allow both risk loadings and performance over a period to be a func- tion of information available at the start of the period. Much of the literature to date has allowed risk loadings to be time-varying while imposing the assumption that conditional performance is constant. We develop a new methodology that allows conditional performance to be a function of information available at the start of the period. This methodology uses the Euler equation restriction that comes out of the factor model rather than the beta pricing formula itself. The Euler equation restrictions that we develop can be estimated using GMM. It is also possible to allow the factor returns to have longer data series than the mutual fund series as in Stambaugh (1997). We use our method to assess the conditional performance of funds in the Elton, Gruber and Blake (1996) mutual fund data set. Using dividend yield to track the business cycle, we nd that conditional mutual fund performance moves with the business cycle, with all fund types except growth performing better in downturns than in peaks. The converse holds for growth funds, which do better in peaks than in downturns

“Interrupt the status quo”: How Black Lives Matter Changed American Museums

Black Lives Matter protests in 2020 were the catalyst for change in many institutions, particularly in museum collections and interpretive methods. This was especially true in museums located in Washington, District of Columbia; Atlanta, Georgia; Portland, Oregon; Los Angeles, California, and Minneapolis, Minnesota. Prior to the protests, most art and history museums upheld a Eurocentric worldview that diminished the contributions of Black Americans. Widespread Black Lives Matter protests, however, forced the discussion of racial equality to the forefront of the American consciousness, encouraging many museums to take a public stance and incorporate Black collective memory into their collections. This thesis analyzes case studies from five American cities that show how museums have utilized the Black Lives Matter Movement’s momentum to create new content for the public

Using Samples of Unequal Length in Generalized Method of Moments Estimation

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent estimators that are consistent, asymptotically normal, and more efficient asymptotically than standard GMM. We apply these methods to estimating predictive regressions in international data and show that the use of the full sample affects point estimates and standard errors for both assets with data available for the full period and assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones.