Moving Toward Social Justice in Sport: A Comprehensive Study of Social Justice Activists in Sport and the Factors that Shape them

There are many different types of injustices in society, and there is no exception for the sport field. Injustices have a negative impact on many aspects of sport. This has resulted in many researchers and former and current athletes realizing that social change effort within their field of interest is necessary. Therefore, the purpose of this dissertation was to describe the psychological processes associated with individuals' interest in and commitment to social justice and why people get involved in social justice advocacy. In this study, I used purposeful sampling, interviewing 11 social justice activists (current and former) in the field of sport or scholars studying the sport industry. The participants were asked what factors have influenced their social justice advocacy and why they got interested in social justice endeavors. First, participants offered their definitions of social justice advocacy, two major themes emerged, the Social Conscience and the Champions of a Cause. Next, the first research question asked of the participants was regarding how they learned about the injustice, which inspired them to become activists in the first place. Three clear themes were identified, direct experience, indirect experience, and indirect contact. In addition, the second research question focused on exploring how activists got involved in social justice advocacy. Three factors were identified, including increased awareness, atypical experience, and emotional responses. Moreover, research question 3 focused on what activities participants are engaged. Three major themes were emerged, raising awareness and changing attitudes, engaging in activity, and encouraging others. Finally, the last research question focused on how activists’ personalities play a role in their activism. In drawing from the big five personality, I identified extraversion, empathetic, and conscientiousness as influential personality traits. In conclusion, I provided a number of practical implications. Especially, participants were influenced by the hardship experienced by others. Therefore, it is possible that exposing students, athletes, or others within your sphere of influence to the impact injustices have to those who live them on a daily basis could provide them with the direct or indirect contact with injustice needed to motivate them to learn more about the issues and encourage them to become involved in change

Differences among Asians and White Americans in Racial Prejudice: A Function of Contact with Out-group Members

In examining the racism in sport literature, two general trends emerge: (a) a focus on Western sport organizations and the prejudice expressed by Whites in these entities; and (b) the tendency to document the occurrence of prejudice without examining key antecedent conditions. The purpose of this study was to address these gaps in the literature. Specifically, I compare the racial prejudice of White Americans with Asians and also examine the degree to which intergroup contact impacts this level of prejudice. Data were collected from Asian (n = 104) and White American (n = 100) college students. They completed a questionnaire that assessed their contact with African Americans as both team mates and exercise partners, their intergroup anxiety, and racial prejudice. Results indicate that all of the study variables were significantly correlated with one another. As expected, a multivariate analysis of variance further illustrated that Asians, relative to Whites, expressed more anxiety and prejudice, while also having less contact with African Americans. Finally, results from a moderated regression indicated that the relationship between nationality and intergroup anxiety was moderated by contact with African Americans as team mates and as exercise partners. In both cases, the lack of contact resulted in greater anxiety for Asians than it did for Whites. This study contributes to the literature by explicitly examining racial bias across cultures. In addition, the findings point to the importance of diversity in exercise and team settings as a way of reducing racial prejudice. That is, since in being contact with African Americans as team mates and exercise partners helped to reduce intergroup anxiety, efforts should be made to increase racial diversity in exercise and sport team settings

Value-Aided Conditional Supervised Learning for Offline RL

Offline reinforcement learning (RL) has seen notable advancements through return-conditioned supervised learning (RCSL) and value-based methods, yet each approach comes with its own set of practical challenges. Addressing these, we propose Value-Aided Conditional Supervised Learning (VCS), a method that effectively synergizes the stability of RCSL with the stitching ability of value-based methods. Based on the Neural Tangent Kernel analysis to discern instances where value function may not lead to stable stitching, VCS injects the value aid into the RCSL's loss function dynamically according to the trajectory return. Our empirical studies reveal that VCS not only significantly outperforms both RCSL and value-based methods but also consistently achieves, or often surpasses, the highest trajectory returns across diverse offline RL benchmarks. This breakthrough in VCS paves new paths in offline RL, pushing the limits of what can be achieved and fostering further innovations

Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making

The recent success of Transformer in natural language processing has sparked its use in various domains. In offline reinforcement learning (RL), Decision Transformer (DT) is emerging as a promising model based on Transformer. However, we discovered that the attention module of DT is not appropriate to capture the inherent local dependence pattern in trajectories of RL modeled as a Markov decision process. To overcome the limitations of DT, we propose a novel action sequence predictor, named Decision ConvFormer (DC), based on the architecture of MetaFormer, which is a general structure to process multiple entities in parallel and understand the interrelationship among the multiple entities. DC employs local convolution filtering as the token mixer and can effectively capture the inherent local associations of the RL dataset. In extensive experiments, DC achieved state-of-the-art performance across various standard RL benchmarks while requiring fewer resources. Furthermore, we show that DC better understands the underlying meaning in data and exhibits enhanced generalization capability

In-situ micromotion compensation of trapped ions by Rabi oscillation and direct scanning of dc voltages

Micromotion is detrimental to accurate qubit control of trapped ions, thus measuring and minimizing it is crucial. In this paper, we present a simple method to measure and minimize micromotion of trapped ions by Rabi oscillation combined with direct scanning of dc voltages. The approach utilizes the qubit control scheme itself, and eliminates the need to install additional experimental setups, or compromise the trapping stability by adjusting the intensity or frequency of the trapping lasers or fields. Accordingly, the method enables in-situ measurement of micromotion during qubit controls of the ions, while achieving a comparable level of sensitivity to commonly used techniques.Comment: 11 pages, 6 figures, submitted to Optics Expres