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Abandonment in the classroom: Urban education, internalized racism, and the school-to-prison pipeline
No full textThis qualitative study used BlackCrit theory to elucidate how white supremacist thinking plays out in Black teachers’ perceptions of and practices with students with chronic disciplinary patterns. Black teachers’ perceptions of Black students are critical to understand because Black students experience disciplinary actions, classroom push-outs, and special education referrals at a disproportionate rate. Internalized racism and racial battle fatigue are consequences of racism experienced by Black educators. Their daily experiences with racism impact how they interact with and view their Black students
“Roots with wings”: Impacts of tourism-induced mobility on individuals and family ties among the Miao in China’s individualization process
No full textThis article looks at the impacts of mobility on individuals and their family ties in tourist destination communities, paying attention to the individualization process among the rural, ethnic minority population in contemporary China. Based on my decade-long ethnography in Fenghuang county, Hunan province, I explore how the rapid rise of tourism-induced mobility has brought individual autonomy and collective morality under constant negotiation among previously clan-based people, and what the course and consequences of ongoing individualization are for the non-Han population in China. I argue that individuals’ greater mobility may enhance, rather than diminish, the importance of family, and that this is especially true for the rural, ethnic minority population in China. Their experience of dealing with individualization also reveals that the effect of social structure is to some extent unchanged, representing a case of “embedded individualization.
Highlights from EMU\u27s Winter 2024 Commencement Ceremony
No full textWatch highlights from Eastern Michigan University\u27s Winter 2024 Commencement Ceremony. The ceremony took place on Saturday, December 14th, 2024 at the George Gervin GameAbove Center. For more information, visit the Commencement website at https://www.emich.edu/commencement. Congratulations graduates
Adolescent-perceived parent–child negative body talk and disordered eating: Evidence for behavior-specific affective mediators
No full textIntroduction This study examined the mediating role of general negative affect and body-specific negative affect between the association between negative body talk occurring within the mother?daughter relationship and restrained and disinhibited disordered eating. Methods Adolescent girls (N?=?100; Mage?=?14.25; 49.5% White) completed self-report measures of general negative affect (depression and anxiety), body-specific negative affect (body dissatisfaction), and perceptions of the frequency that negative body talk occurred in interactions with their mother (initiated by the mother or daughter) as part of a cross-sectional study. While the same set of questionnaires was administered to both mothers and daughters, only the data reported by the daughters were analyzed and included in this study. Data were gathered in the Ann Arbor/Ypsilanti area of Michigan, USA, around the year 2015. Results Path analysis showed that general negative affect, but not body-specific negative affect, mediated the association from mother?daughter negative body talk to disinhibited eating behaviors (emotional and external eating). Conversely, body-specific negative affect, but not general negative affect, mediated the association from negative body talk to restrained eating behaviors. Conclusions Our findings suggest there are distinct affective mechanisms that mediate the relationship between mother?daughter negative body talk and restrained versus disinhibited eating behavior. Future work should continue to explicate the role of general and body-related negative affect in different eating behaviors
The ethical implications of big data in human resource management
No full textThis article examines the ethical implications of big data in human resource management (HRM) practices, specifically in the areas of recruitment and selection, training and development, performance management, compensation, and employee retention. The article commences with a characterization of big data applications in HRM processes and practices, highlighting their benefits and value for the management of the workforce. It also shows how the application of big data analytics can put employees at great risk through institutional surveillance and other algorithmic manipulation practices such as profiling, coercion and control. Our theorizing advances the HRM and ethics literatures by offering a more expanded and nuanced view of the significant ethical challenges specific to individual HR practices. Additionally, our analysis brings ethics into the domain of HRM by problematizing the exploitation of employee information through digital technology for corporate gain. In so doing, it employs a moral principles framework to show how BDA - HRM practices can compromise employees\u27 rights to privacy, confidentiality, transparency, and protection. Our analysis also raises concerns shared by both the practitioner and scholarly communities that are yet to be addressed and offers recommendations for research and practice
Generating functions and counting formulas for spanning trees and forests in hypergraphs
No full textIn this paper, we provide generating functions and counting formulas for spanning trees and spanning forests in hypergraphs in two different ways: (1) We represent spanning trees and spanning forests in hypergraphs through BerezinGrassmann integrals on Zeon algebra and hyper-Hafnians (orders and signs are not considered); (2) We establish a HyperPfaffian-Cactus Spanning Forest Theorem through BerezinGrassmann integrals on Grassmann algebra (orders and signs are considered), which generalizes the Hyper-Pfaffian-Cactus Theorem by Abdesselam (2004) [1] and Pfaffian matrix tree theorem by Masbaum and Vaintrob (2002) [15]. (c) 2024 Elsevier Inc. All rights reserved
A comparative sentiment analysis of airline customer reviews using Bidirectional Encoder Representations from Transformers (BERT) and its variants
No full textThe applications of artificial intelligence (AI) and natural language processing (NLP) have significantly empowered the safety and operational efficiency within the aviation sector for safer and more efficient operations. Airlines derive informed decisions to enhance operational efficiency and strategic planning through extensive contextual analysis of customer reviews and feedback from social media, such as Twitter and Facebook. However, this form of analytical endeavor is labor-intensive and time-consuming. Extensive studies have investigated NLP algorithms for sentiment analysis based on textual customer feedback, thereby underscoring the necessity for an in-depth investigation of transformer architecture-based NLP models. In this study, we conducted an exploration of the large language model BERT and three of its derivatives using an airline sentiment tweet dataset for downstream tasks. We further honed this fine-tuning by adjusting the hyperparameters, thus improving the model’s consistency and precision of outcomes. With RoBERTa distinctly emerging as the most precise and overall effective model in both the binary (96.97%) and tri-class (86.89%) sentiment classification tasks and persisting in outperforming others in the balanced dataset for tri-class sentiment classification, our results validate the BERT models’ application in analyzing airline industry customer sentiment. In addition, this study identifies the scope for improvement in future studies, such as investigating more systematic and balanced datasets, applying other large language models, and using novel fine-tuning approaches. Our study serves as a pivotal benchmark for future exploration in customer sentiment analysis, with implications that extend from the airline industry to broader transportation sectors, where customer feedback plays a crucial role
Growth trajectories and roles of expectancy, task value, and cost in middle-school physical education
No full textThis longitudinal investigation tracked the progression of students’ expectancy for success, task value, and perceived cost in the context of physical education throughout an academic year. The study involved 399 middle-school students from China, and data were collected at three distinct time points. Analysis using latent growth curve models revealed positive trajectories in both expectancy and task value, along with decreases in perceived cost. Variations in motivation were observed based on demographic factors, both in initial motivation levels and change rate. At the beginning of the academic year, senior students, girls, and students who were overweight exhibited lower motivation compared to their counterparts, but these motivation disparities tended to reduce over time. Changes in motivation were significant predictors of learning outcomes. Students who sustained high levels of expectancy and task value while reducing their perceived effort cost demonstrated higher cardiorespiratory fitness. The findings expand the theoretical understanding of expectancy, task value, and cost, thereby supporting the feasibility of implementing programmatic interventions to bolster motivation in physical education