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School climate is a construct frequently explored in educational research (Lee, Cornell, Gregory, & Fan, 2011; Wang & Degol, 2016) and is associated positive several outcomes including with improved student-teacher relationships (Croninger & Lee, 2001) and reduced school dropout risk (Jia, Konold, & Cornell, 2016). Unfortunately, emerging research indicates that racial differences in schools’ penal practices may be negatively coupled with Black students’ experience of a supportive school climate (Bottiani, Bradshaw, & Mendelson, 2017). Black students are disproportionately subjected to exclusionary disciplinary practices (e.g., suspensions and expulsions) in the learning environment (Fenning & Rose, 2007) and Black girls disproportionally encounter more adverse disciplinary outcomes in their educational setting (National Black Women’s Justice Institute, 2018) relative to their White peers (Blake, Butler, Lewis, & Darensbourg, 2011; Crenshaw, Ocen, & Nanda, 2015; Epstein, Blake, & González, 2017; Hines-Datiri & Carter Andrews, 2017). Persistent use of punitive practices may hinder Black girls’ racial identity, academic, and social-emotional development in the classroom (Chavous, Rivas-Drake, Smalls, Griffin, & Cogburn, 2008; Leath, Mathews, Harrison, & Chavous, 2019) and consequently detrimentally impact their school climate. Researchers have called for evidence-based and culturally relevant interventions that promote positive academic outcomes for Black girls (Jones et al., 2018). However, evidence-based interventions are dependent on the use of empirically supported assessments with diverse student groups (Pendergast et al., 2017). Evidence-based assessments are necessary to identify students’ needs in the educational setting and provide baseline data that allow for the evaluation of intervention effectiveness. Moreover, school climate assessments for Black girls may facilitate the development of evidence-based interventions for Black girls - who are disproportionally disciplined and may be at risk of experiencing a negative school climate. This study investigated the structural validity and reliability of scores from a school climate measurement tool. The study examined measurement invariance of the Student Connection Survey, with a specific focus on Black girls’ scores. Results indicated the Student Connection Survey is represented by five-latent factors and is equivalent between Black and White middle school girls. Implications, strengths, limitations, and future research directions are discussed. / School Psychology

Asians consistently report higher social anxiety symptoms but have lower prevalence rates, compared to Westerners. As cultural differences and measurement issues could both be potential sources for the discrepancy, it is important to examine whether score differences between cultural groups are due to measurement issues or genuine underlying differences in social anxiety. This study used 402 participants to examine the construct of social anxiety and measurement invariance of six social anxiety scales using exploratory and confirmatory factor analysis. Results supported scalar invariance of a three-factor bifactor model (comprised of Fear/Avoidance of Social Interaction, Fear of Negative Evaluation, and Taijin Kyofusho/fear of interpersonal relationships). Furthermore, multivariate analysis of covariance and moderation analysis revealed Asian Americans endorsed higher Fear/Avoidance of Social Interaction symptoms, but do not differ in Taijin Kyofusho and Fear of Negative Evaluation symptoms, compared to European Americans. This study showed when measurement bias is minimized, Asians still endorse higher symptoms of Fear/Avoidance of Social Interactions. Moreover, Taijin Kyofusho appears to be an aspect of social anxiety identified in more than one cultural group rather than a culture-related specific syndrome. Thus, it is important for clinicians and researchers to consider Taijin Kyofusho in the evaluation of social anxiety. / School Psychology

The focus of this dissertation is imperfectly competitive sports labor markets and the effects of league labor policy on player mobility, compensation, and job location choice. The analyses conducted herein contributes primarily to a broad area of research within sports economics that generally uses changes in league labor rules to examine employer monopsony power and the validity of the Invariance Principle, which states that the distribution of playing talent in a sports league is invariant to the ownership of the rights to players’ services. After a critical review of the literature and some background on the National Basketball Association (NBA), a broad-to-narrow approach is used to present evidence from three empirical essays. Essay one examines the effects of 40 years’ worth of institutional change on competitive balance in the NBA. Essay two investigates the effects of more recent free agency rules on player mobility and pay. Finally, essay three narrows the focus a bit further to the effects of nonwage job characteristics on player wages and the implications of such nonwage attributes for player movement. / Tourism and Sport

No / The purpose of this paper is to highlight the importance of constraints in the theory of relativity and, in particular, what philosophical work they do for Einstein's views on the laws of physics. Einstein presents a view of local ``structure laws'' which he characterizes as the most appropriate form of physical laws. Einstein was committed to a view of science, which presents a synthesis between rational and empirical elements as its hallmark. If scientific constructs are free inventions of the human mind, as Einstein, held, the question arises how such rational constructs, including the symbolic formulation of the laws of physics, can represent physical reality. Representation in turn raises the question of realism. Einstein uses a number of constraints in the theory of relativity to show that by imposing constraints on the rational elements a certain ``fit'' between theory and reality can be achieved. Fit is to be understood as satisfaction of constraint. His emphasis on reference frames in the STR and more general coordinate systems in the GTR, as well as his emphasis on the symmetries of the theory of relativity suggests that Einstein's realism is akin to a certain form of structural realism. His version of structural realism follows from the theory of relativity and is independent of any current philosophical debates about structural realism.

Yes / The essay revisits the puzzle of the ‘passage’ of time in relation to EPR-type measurements and asks what philosophical consequences can be drawn from them. Some argue that the lack of invariance of temporal order in the measurement of a space-like related EPR pair, under relativistic motion, casts serious doubts on the ‘reality’ of the lapse of time. Others argue that certain features of quantum mechanics establish a tensed theory of time – understood here as Possibilism or the growing block universe. The paper analyzes the employment of frame-invariant entropic clocks in a relativistic setting and argues that tenselessness does not imply timelessness. But this conclusion does not support a tensed theory of time, which requires a preferred foliation. It is argued that the only reliable inference from the EPR example and the use of entropic clocks is an inference not just to a Leibnizian order of the succession of events but a frame-invariant order according to some selected clocks.

<p dir="ltr">Despite their astonishing capacity to fit data, neural networks have difficulties extrapolating beyond training data distribution. When the out-of-distribution prediction task is formalized as a counterfactual query on a causal model, the reason for their extrapolation failure is clear: neural networks learn spurious correlations in the training data rather than features that are causally related to the target label. This thesis proposes to perform a causal search over a known family of causal models to learn robust (maximally invariant) predictors for single- and multiple-environment extrapolation tasks.</p><p dir="ltr">First, I formalize the out-of-distribution task as a counterfactual query over a structural causal model. For single-environment extrapolation, I argue that symmetries of the input data are valuable for training neural networks that can extrapolate. I introduce Asymmetry learning, a new learning paradigm that is guided by the hypothesis that all (known) symmetries are mandatory even without evidence in training, unless the learner deems it inconsistent with the training data. Asymmetry learning performs a causal model search to find the simplest causal model defining a causal connection between the target labels and the symmetry transformations that affect the label. My experiments on a variety of out-of-distribution tasks on images and sequences show that proposed methods extrapolate much better than the standard neural networks.</p><p dir="ltr">Then, I consider multiple-environment out-of-distribution tasks in dynamical system forecasting that arise due to shifts in initial conditions or parameters of the dynamical system. I identify key OOD challenges in the existing deep learning and physics-informed machine learning (PIML) methods for these tasks. To mitigate these drawbacks, I combine meta-learning and causal structure discovery over a family of given structural causal models to learn the underlying dynamical system. In three simulated forecasting tasks, I show that the proposed approach is 2x to 28x more robust than the baselines.</p>

The present work in the area of soliton theory studies two problems which arise when seeking analytic solutions to certain nonlinear partial differential equations. In the first one, Lax pairs associated with prolonged eigenfunctions and prolonged squared eigenfunctions (prolonged squares) are derived for a Schrödinger equation with a potential depending polynomially on the spectral parameter (of degree N) and its respective hierarchy of nonlinear evolution equations (here named generalized polynomial Korteweg-de Vries equations or GPKdV). It is shown that the prolonged squares satisfy the linearized GPKdV equations. On that basis, the Cauchy problem for the linearized GPKdV has been solved by finding a complete set of such prolonged squares and applying an expansion formula derived in another work by the author. The results are a generalization of the ones by Sachs (SIAM J. Math. Anal. 14, 1983, 674-683). Moreover, a condition on the so-called recursion operator A is derived which generates the whole hierarchy of Lax pairs associated with the prolonged squares. As for the second part of the work, it developed a scheme for deriving gauge transformations between different linear spectral problems. Then the scheme is applied to obtain all known Darboux transformations for a quadratic pencil (the spectral problem considered in the first part at N = 2), Schrödinger equation (N = 1), Ablowitz-Kaup-Newell-Segur (AKNS) system and also derive the Jaulent-Miodek transformation. Moreover, the scheme yields a large family of new transformations of the above types. It also gives some insight on the structure of the transformations and emphasizes the symmetry with respect to inversion that they possess. / Ph. D.

Previous research has been limited regarding the measurement of computational thinking, particularly as a learning progression in K-12. This study proposes to apply a multidimensional item response theory (IRT) model to a newly developed measure of computational thinking utilizing both selected response and open-ended polytomous items to establish the factorial structure of the construct, apply the recently introduced composite and structured constructs models, and to investigate the measurement invariance of the assessment between males and females using the means and covariance structures (MACS) approach.

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