15,494 research outputs found
Sean Rubin: Cook Prize 2025, Silver Medal Acceptance Speech
No full textAuthor and illustrator Sean Rubin gives an acceptance speech for The Iguanodon’s Horn (Clarion/HarperCollins)https://educate.bankstreet.edu/cook/1015/thumbnail.jp
Who Are Athletic Advisors? State of the Profession
No full textCitation: Lisa M. Rubin (2017) Who Are Athletic Advisors? State of the Profession. NACADA Journal: 2017, Vol. 37, No. 1, pp. 37-50.The field of athletic advising has existed since the 1970s. In the early 1990s, the National Collegiate Athletic Association mandated that higher education institutions provide academic support for student-athletes. Few researchers have identified those serving as athletic advisors, so the literature features little data on advisor demographics, training, education, and work responsibilities. Therefore, the background and experiences of 277 members of the National Association of Academic Advisors for Athletics, who responded to a survey, were explored. Specifically, athletic advisor educational and training background, burnout levels, meaning of the profession as participants describe it, advice for prospective advisors, and the knowledge they wish they had gained before entering the field are addressed. Dramaturgy was utilized as a framework for analyzing this research
In the Highest Degree Ominous: Hitler's Threatened Invasion and the British War Zone Courts
No full text"Improving the Rank-Adjusted Anderson-Rubin Test with Many Instruments and Persistent Heteroscedasticity"
No full textAnderson and Kunitomo (2007) have developed the likelihood ratio criterion, which is called the Rank-Adjusted Anderson-Rubin (RAAR) test, for testing the coefficients of a structural equation in a system of simultaneous equations in econometrics against the alternative hypothesis that the equation of interest is identified. It is related to the statistic originally proposed by Anderson and Rubin (1949, 1950), and also to the test procedures by Kleibergen (2002) and Moreira (2003). We propose a modified procedure of RAAR test, which is suitable for the cases when there are many instruments and the disturbances have persistent heteroscedasticities.
Reflections on the Undergraduate Research Experience of Three Former NCAA Division I Athletes
No full textUndergraduate research (UR) opportunities are important for college students to engage in areas of interest, gain valuable skills, and contribute to their learning outside of the classroom (Mahatmya et al., 2017). There have been a few studies on college athletes engaged in high impact practices (HIPs) like study abroad programs (Navarro et al., 2020), first-year seminars (Grafnetterova et al., 2020), and learning communities (Mamerow & Navarro, 2014). However, little has been studied on athletes’ engagement in UR (also a HIP). While athletes may not be a large percentage of an institution’s student population, they are more visible in the campus community. College athletes face time constraints, balancing two full-time roles of student and athlete, often with limited time remaining to devote to extracurricular activities (Ishaq & Bass, 2019; Rubin & Moses, 2017). They also endure negative stereotypes, seen as outsiders by the student body and faculty, isolating themselves from campus involvement (Rubin & Moses, 2017; Simons et al., 2020). These stereotypes include the idea of the “dumb jock,” in which athletes are incapable of handling collegelevel work and require additional support to pass classes (Simons et al., 2007). Many campuses offer academic support in facilities designated specifically for athletes, beyond the typically weekday work hours (Rubin & Moses, 2017). Besides attending classes on campus, athletes spend most of their time in athletic facilities for meals, workouts, tutoring, and practices. In classes, they are more likely to sit with other athletes who understand their schedule and lifestyle (Rubin & Moses, 2017). Their rigid schedules might prohibit them from exploring student organizations or UR. Because of this, engaging athletes in UR is not as easy or obvious for faculty as it may be with other students. Yet, Gaston-Gayles and Hu (2009) discovered that athletes who engage in educationally purposeful activities, including faculty interaction and collaborative learning, improve in cognitive and academic outcomes. Since athletes’ college experience may differ significantly from that of other students, it is important to learn from former athletes’ participation in UR
Abschriften aus mittelalterlichen Liederhandschriften / Her Walther von Metze, "Ehrlich und treu"; I.165b. - Her Rubin, "Tageliet"; I.171a. - K 3123,54,2 : Abschrift aus mittelalterlicher Liederhandschrift : Schreiber: Laßberg, Joseph von (1770-1855)
No full textFrühere Signatur: K 3123,7,2Inhalt: Abschrift eines Minneliedes des Walther von Metz und eines Tageliedes des Sängers Rubin aus dem Codex Manesse. - Zitierte Personen: Gossouin ; Rubin. - Zitiertes Werk: Manessische Handschrift. - Vorbesitzer: Braun, Emil. - Schreiber: Laßberg, Joseph vo
Athletic Subculture within Student-Athlete Academic Centers
No full textCitation: Rubin, L. R., & Moses, R. A. (2017). Athletic Subculture within Student-Athlete Academic Centers. Sociology of Sport Journal. (Forthcoming). http://dx.doi.org/10.1123/ssj.2016-0138Over 400,000 student-athletes participate in NCAA intercollegiate athletics programs. Due to their dual roles as student and athlete, they have a different college experience than the general student population. Specialized academic centers and resources for student-athletes are part of the reason they are separated and often isolated from the rest of campus. Teams have their own unique academic subculture that influences each student-athlete in his or her academic pursuits. The purpose of this study is to explore the athletic academic subculture among student-athletes at the Division I level and the role the athletic academic center and special resources play in cultivating a separate culture from the campus culture. Symbolic interactionism was the framework used as the lens to view the results of this study in the context of neoliberalism
Approximate Nearest Neighbor Search Amid Higher-Dimensional Flats
No full textWe consider the Approximate Nearest Neighbor (ANN) problem where the input set consists of n k-flats in the Euclidean Rd, for any fixed parameters k 0 is another prespecified parameter. We present an algorithm that achieves this task with n^{k+1}(log(n)/epsilon)^O(1) storage and preprocessing (where the constant of proportionality in the big-O notation depends on d), and can answer a query in O(polylog(n)) time (where the power of the logarithm depends on d and k). In particular, we need only near-quadratic storage to answer ANN queries amidst a set of n lines in any fixed-dimensional Euclidean space. As a by-product, our approach also yields an algorithm, with similar performance bounds, for answering exact nearest neighbor queries amidst k-flats with respect to any polyhedral distance function. Our results are more general, in that they also
provide a tradeoff between storage and query time
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