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Why Teachers Stay: A Multiple Case Study Of Retention In Small To Midsized Schools, Karen Shaw Ewton May 2025

Why Teachers Stay: A Multiple Case Study Of Retention In Small To Midsized Schools, Karen Shaw Ewton

Electronic Theses and Dissertations

Teacher retention presents a critical challenge for small to midsized school districts, often compounded by limited resources and unique community dynamics. Using Herzberg’s twofactor theory, this qualitative study explored factors influencing teacher retention in districts with retention rates exceeding 85%. Semistructured interviews with nine teachers examined the impact of hygiene factors, such as administrative support and compensation, and motivators, like autonomy and professional growth. Thematic analysis revealed that administrative support and equitable workloads prevent dissatisfaction, while motivators such as meaningful relationships, recognition, and relevant professional development drive commitment. Professional development emerged as both a motivator and a hygiene factor based …

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The Effects Of Loving-Kindness Meditation (Lkm) On Relationship Satisfaction In Couple Therapy, Ruimeng Gao May 2025

The Effects Of Loving-Kindness Meditation (Lkm) On Relationship Satisfaction In Couple Therapy, Ruimeng Gao

Electronic Theses and Dissertations

This thesis explores the integration of loving-kindness meditation (LKM) into couple therapy sessions and its impact on relationship satisfaction. Meditation, historically rooted in religious practices, has increasingly been adopted in Western therapeutic contexts due to its demonstrated benefits for mental health and interpersonal well-being. Although mindfulness-based interventions have gained popularity in psychotherapy, research specifically examining the use of LKM in couple therapy remains limited. This study investigates whether incorporating LKM into therapy sessions enhances relationship satisfaction compared to standard therapy alone. Couples were randomly assigned to either a control group, which received standard therapy, or an experimental group, which practiced …

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Shipnavisim: Data-Driven Simulation For Real-World Maritime Navigation, Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar May 2025

Shipnavisim: Data-Driven Simulation For Real-World Maritime Navigation, Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar

Research Collection School Of Computing and Information Systems

Maritime traffic management in busy ports faces growing challenges due to increased vessel traffic and complex waterway interactions. Strategies such as e-navigation by the International Maritime Organization aim to enhance navigation safety through traffic digitization. Maritime traffic simulation is essential for these systems, offering a virtual environment to model, analyze, and optimize traffic flows. Unlike road traffic, there are few simulators for maritime traffic, and they often lack realism and multi-ship interactions. In this paper, we (a) present ShipNaviSim, a data-driven maritime traffic simulator that utilizes a large-scale dataset over 2 years and electronic navigation charts to model vessel movements …

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Few-Shot Learning On Graphs: From Meta-Learning To Llm-Empowered Pre-Training And Beyond, Yuan Fang, Yuxia Wu, Xingtong Yu, Shirui Pan May 2025

Few-Shot Learning On Graphs: From Meta-Learning To Llm-Empowered Pre-Training And Beyond, Yuan Fang, Yuxia Wu, Xingtong Yu, Shirui Pan

Research Collection School Of Computing and Information Systems

Graph representation learning has become central to many graph-based tasks, driving advancements in various domains such as web search, recommendation systems, and social network analysis. Traditionally, these methods rely on end-to-end supervised learning paradigms that require abundant labeled data, which can be costly and difficult to obtain. To address this limitation, few-shot learning on graphs has emerged as a promising approach, allowing models to generalize with minimal supervision and overcome data scarcity in real-world applications. This tutorial offers an in-depth exploration of recent advancements in few-shot learning for graphs, providing a comparative analysis of state-of-the-art methods and identifying future research …

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“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono May 2025

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

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Unlocking The Planning Capabilities Of Llms Through Maximum Diversity Fine-Tuning, Wenjun Li, Changyu Chen, Pradeep Varakantham May 2025

Unlocking The Planning Capabilities Of Llms Through Maximum Diversity Fine-Tuning, Wenjun Li, Changyu Chen, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated impressive task-solving capabilities through prompting techniques and system designs, including solving planning tasks (e.g., math proofs, basic travel planning) when sufficient data is available online and used during pre-training. However, for planning tasks with limited prior data (e.g., blocks world, advanced travel planning), the performance of LLMs, including proprietary models like GPT and Gemini, is poor. This paper investigates the impact of fine-tuning on the planning capabilities of LLMs, revealing that LLMs can achieve strong performance in planning through substantial (tens of thousands of specific examples) fine-tuning. Yet, this process incurs high economic, time, …

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Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham May 2025

Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in developing such tools is in exploring how mastery can be achieved across a diverse yet related range of content in an efficient manner. While Reinforcement Learning and Multi-armed Bandits have shown promise in educational settings, existing works often assume the independence of learning content, neglecting the prevalent interdependencies between such content. In response, we introduce Education Network Restless Multi-armed Bandits (EdNetRMABs), utilizing a network to represent the relationships between interdependent arms. Subsequently, we propose …

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2025 May, Morehead State University. Office Of Communications & Marketing. May 2025

2025 May, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for May of 2025.

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Apala Best Of The Best Booklist 2023 - 2024, Asian Pacific American Librarians Association, Family Literacy Focus Committee, Education Subcommittee, Jessea Young (Chair), Zoë Bowlus, Nicole Fernandez, Erika Fitzpatrick, Cathy Lin, Kim Nguyen, Patty Sumire Mcgowan, Yer Vang May 2025

Apala Best Of The Best Booklist 2023 - 2024, Asian Pacific American Librarians Association, Family Literacy Focus Committee, Education Subcommittee, Jessea Young (Chair), Zoë Bowlus, Nicole Fernandez, Erika Fitzpatrick, Cathy Lin, Kim Nguyen, Patty Sumire Mcgowan, Yer Vang

Librarian Publications & Presentations

Started in 2022, the Best of the Best Booklist celebrates stories from across the Asian American, Native Hawaiian, and Pacific Islander (AANHPI) diaspora. All APALA members were invited to nominate picture book titles about AANHPI communities and experiences that were published in the 2023 and 2024 calendar years. To curate the final list, members of the APALA Family Literacy Focus Committee evaluated the nominations, guided by the mission of Talk Story and APALA Rubric to Evaluate Asian American and Pacific Islander Youth Literature. The committee is grateful to all the members who nominated titles. Eligible titles that earned a …

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Fostering Ai Literacy In Undergraduates: A Chatgpt Workshop Case Study, Susan G. Archambault, Nicole L. Murph, Shalini Ramachandran May 2025

Fostering Ai Literacy In Undergraduates: A Chatgpt Workshop Case Study, Susan G. Archambault, Nicole L. Murph, Shalini Ramachandran

Librarian Publications & Presentations

This case study explores the design and implementation of a Chat-GPT literacy workshop for undergraduate students, aiming to equip them with the skills and knowledge necessary to navigate the AI-driven information landscape responsibly and critically. Drawing from a comprehensive literature review on AI literacy and employing a postphenomenological lens, the workshop incorporated best practices for teaching ChatGPT skills, including an emphasis on ethical considerations and critical reflection on the human-technology relationship. The postphenomenological perspective allows for a deeper understanding of how ChatGPT shapes students' experiences and practices. Employing a mixed-methods approach, the study assessed the effectiveness of the workshop through …

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Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch May 2025

Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch

College Honors Program

Zoning is a powerful regulatory tool that determines how municipalities use and develop land. The goal of zoning is to classify land use (e.g., residential, commercial, industrial) to maximize compatibility among neighboring parcels. Local zoning decisions, however, are made by small-sized boards, often through an opaque process, which raises concerns about bias and fairness. In the United States, zoning has historically prioritized single-family housing and thus created economic barriers that limit access to certain communities. Given the task of classifying land use and the wealth of geographical, demographic, and infrastructural data describing each parcel, the problem of bias in zoning …

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The State Of Latino-Serving Community-Based Organizations In Massachusetts, Fabián Torres-Ardila, Phillip Granberry, Rachel Paz, Luna Páez Abaunsa, Valentina Valderrama Pérez May 2025

The State Of Latino-Serving Community-Based Organizations In Massachusetts, Fabián Torres-Ardila, Phillip Granberry, Rachel Paz, Luna Páez Abaunsa, Valentina Valderrama Pérez

Gastón Institute Publications

Massachusetts has a diverse Latino population with large numbers of Puerto Ricans, Dominicans, Salvadorans, Guatemalans, and Mexicans. Nearly a third (32%) of the Latino population is foreign-born. Of this foreign-born population, 61% are not U.S. citizens. Nearly 210,000 Latino children are enrolled in K-12 schools. Of the Latino population over age five who speak Spanish in the home, 33% have limited English proficiency. Among the adult population, 28% have less than a high school education, and 60% are in the labor force.3 The varied needs of this population require a strong ecosystem of local organizations that provide services to support …

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Limitations Due To Occupational Credentialing For Immigrants In Massachusetts: Survey Report, Phillip Granberry, Florita Coto Tristán, Fabián Torres-Ardila, Jonathan Vega-Martinez, Maria M. Pache De Athayde May 2025

Limitations Due To Occupational Credentialing For Immigrants In Massachusetts: Survey Report, Phillip Granberry, Florita Coto Tristán, Fabián Torres-Ardila, Jonathan Vega-Martinez, Maria M. Pache De Athayde

Gastón Institute Publications

The Gastón Institute began investigating occupational credentialing because of a previous research project with English for New Bostonians, which had found that many people in its ESOL (English for Speakers of Other Languages) classes complained that lack of an occupational credential had caused them to suffer unemployment or underemployment. The Latino Equity Fund at the Boston Foundation provided the funding for a study addressing the problem of determining the extent to which Massachusetts immigrants are having trouble in the labor market because they lack the proper occupational credentials. The study has two complementary components: a qualitative study with interviews of …

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Reverse Modeling In Large Language Models, Sicheng Yu, Yuanchen Xu, Cunxiao Du, Yanying Zhou, Minghui Qiu, Qianru Sun, Hao Zhang, Jiawei Wu May 2025

Reverse Modeling In Large Language Models, Sicheng Yu, Yuanchen Xu, Cunxiao Du, Yanying Zhou, Minghui Qiu, Qianru Sun, Hao Zhang, Jiawei Wu

Research Collection School Of Computing and Information Systems

Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in auto-regressive large language models (LLMs). This paper investigates whether LLMs, like humans, struggle with reverse modeling, specifically with reversed text inputs. We found that publicly available pre-trained LLMs cannot understand such inputs. However, LLMs trained from scratch with both forward and reverse texts can understand them equally well during inference. Our case study shows that different-content texts result in different losses if input (to LLMs) in different directions---some get lower losses for forward while some for reverse. This leads us …

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Guest Editorial: When Multimedia Meets Food: Multimedia Computing For Food Data Analysis And Applications, Weiqing Min, Shuqiang Jiang, Petia Radeva, Vladimir Pavlovic, Chong-Wah Ngo, Kiyoharu Aizawa, Wanqing Li May 2025

Guest Editorial: When Multimedia Meets Food: Multimedia Computing For Food Data Analysis And Applications, Weiqing Min, Shuqiang Jiang, Petia Radeva, Vladimir Pavlovic, Chong-Wah Ngo, Kiyoharu Aizawa, Wanqing Li

Research Collection School Of Computing and Information Systems

Food is central in our life for its fundamental role in our survival, health, mood and culture. The deployment of various networks (e.g., IoT and mobile networks), devices (e.g., hyperspectral imaging devices, electronic nose/tongue), databases (e.g., nutrition tables and food compositional databases), recipe-sharing websites (e.g., Yummly and Meishijie) and social media (e.g., Twitter and Weibo) has generated unprecedented volumes of multi-modal food data. Such multi-source multi-modal food data provides new perspectives to analyze and understand food consumption via multimedia computing. Riding on the wave of AI, food-oriented multimedia computing integrates AI, multimedia technology and food science to enable a wide …

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Fixdrive: Automatically Repairing Autonomous Vehicle Driving Behaviour For $0.08 Per Violation, Yang Sun, Christopher M. Poskitt, Kun Wang, Jun Sun May 2025

Fixdrive: Automatically Repairing Autonomous Vehicle Driving Behaviour For $0.08 Per Violation, Yang Sun, Christopher M. Poskitt, Kun Wang, Jun Sun

Research Collection School Of Computing and Information Systems

Autonomous Vehicles (AVs) are advancing rapidly, with Level-4 AVs already operating in real-world conditions. Current AVs, however, still lag behind human drivers in adaptability and performance, often exhibiting overly conservative behaviours and occasionally violating traffic laws. Existing solutions, such as runtime enforcement, mitigate this by automatically repairing the AV's planned trajectory at runtime, but such approaches lack transparency and should be a measure of last resort. It would be preferable for AV repairs to generalise beyond specific incidents and to be interpretable for users. In this work, we propose FixDrive, a framework that analyses driving records from near-misses or law …

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Intention Is All You Need: Refining Your Code From Your Intention, Qi Guo, Xiaofei Xie, Shangqing Liu, Ming Hu, Xiaohong Li, Lei Bu May 2025

Intention Is All You Need: Refining Your Code From Your Intention, Qi Guo, Xiaofei Xie, Shangqing Liu, Ming Hu, Xiaohong Li, Lei Bu

Research Collection School Of Computing and Information Systems

Code refinement aims to enhance existing code by addressing issues, refactoring, and optimizing to improve quality and meet specific requirements. As software projects scale in size and complexity, the traditional iterative exchange between reviewers and developers becomes increasingly burdensome. While recent deep learning techniques have been explored to accelerate this process, their performance remains limited, primarily due to challenges in accurately understanding reviewers’ intents. This paper proposes an intention-based code refinement technique that enhances the conventional comment-to-code process by explicitly extracting reviewer intentions from the comments. Our approach consists of two key phases: Intention Extraction and Intention Guided Revision Generation. …

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Scenario-Driven And Context-Aware Automated Accessibility Testing For Android Apps, Yuxin Zhang, Sen Chen, Xiaofei Xie, Zibo Liu, Lingling Fan May 2025

Scenario-Driven And Context-Aware Automated Accessibility Testing For Android Apps, Yuxin Zhang, Sen Chen, Xiaofei Xie, Zibo Liu, Lingling Fan

Research Collection School Of Computing and Information Systems

Mobile accessibility is increasingly important nowadays as it enables people with disabilities to use mobile applications to perform daily tasks. Ensuring mobile accessibility not only benefits those with disabilities but also enhances the user experience for all users, making applications more intuitive and user-friendly. Although numerous tools are available for testing and detecting accessibility issues in Android applications, a large number of false negatives and false positives persist due to limitations in the existing approaches, i.e., low coverage of UI scenarios and lack of consideration of runtime context. To address these problems, in this paper, we propose a scenario-driven exploration …

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Acccred: Improved Accountable Anonymous Credentials With Dynamic Triple-Hiding Committees, Sijiang Xie, Rui Shi, Yang Yang, Huiqin Xie, Yingjiu Li, Robert H. Deng May 2025

Acccred: Improved Accountable Anonymous Credentials With Dynamic Triple-Hiding Committees, Sijiang Xie, Rui Shi, Yang Yang, Huiqin Xie, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Accountable anonymous credentials protect user privacy while holding the accountability of ill-intentioned individuals, which is a critical feature for applications such as online payments and other financial services. Existing accountable anonymous credentials rely on a public committee of trustworthy members who are assumed not to collude and are well protected to perform privacy revocation. However, this assumption is unsound in blockchain-based cryptocurrency systems because the selected committees may involve nodes with significant stakes, and public nodes serving as committee members are vulnerable against targeted attacks from high-computing power adversaries. In this paper, we propose an improved accountable anonymous credential called …

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Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-Based Benchmark, Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei May 2025

Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-Based Benchmark, Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei

Research Collection School Of Computing and Information Systems

Empathetic Response Generation (ERG) is one of the key tasks of the affective computing area, which aims to produce emotionally nuanced and compassionate responses to user's queries. However, existing ERG research is predominantly confined to the singleton text modality, limiting its effectiveness since human emotions are inherently conveyed through multiple modalities. To combat this, we introduce an avatar-based Multimodal ERG (MERG) task, entailing rich text, speech, and facial vision information. We first present a large-scale high-quality benchmark dataset, AvaMERG, which extends traditional text ERG by incorporating authentic human speech audio and dynamic talking-face avatar videos, encompassing a diverse range of …

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Iot In Sustainability And Iot In The Ai And Metaverse Age, Yuzhou Qian, Keng Siau May 2025

Iot In Sustainability And Iot In The Ai And Metaverse Age, Yuzhou Qian, Keng Siau

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is a modern technology that has gained large popularity and is still developing. Connecting heterogeneous devices, such as phones, vehicles, and household appliances, IoT has brought convenience to our lives. Further, IoT plays a significant role in enhancing environmental sustainability. It provides timely data about different devices and enables users and managers to directly control the objects. IoT can optimize the existing energy systems and promote the usage of renewable technologies. In this paper, we discuss how IoT supports green initiatives (i.e., how it is applied in different sectors), how it can be "green" itself …

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Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing May 2025

Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing

Research Collection School Of Computing and Information Systems

This study introduces two novel benchmarks, SeaExam and SeaBench, designed to evalu ate the capabilities of Large Language Models (LLMs) in Southeast Asian (SEA) application scenarios. Unlike existing multilingual datasets primarily derived from English translations, these benchmarks are constructed based on real world scenarios from SEA regions. SeaExam draws from regional educational exams to form a comprehensive dataset that encompasses sub jects such as local history and literature. In contrast, SeaBench is crafted around multi turn, open-ended tasks that reflect daily inter actions within SEA communities. Our evalua tions demonstrate that SeaExam and SeaBench more effectively discern LLM performance on …

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Scar Reveal, Danielle A. Unger May 2025

Scar Reveal, Danielle A. Unger

LSU New Orleans Theses and Dissertations

Scar Reveal is a collection of twenty-eight poems. The author arranges the poems in three sections that explore the family of origin and religion, mental health and mortality, and love and labor. The collection is preceded by a preface essay where the author discusses her relationship with poetry and how her poetics have developed throughout her mental health recovery and work as a therapist. The author also provides a brief overview of some selected craft techniques and influences within the manuscript.

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The Deterrence Effects Of Tax Whistleblower Laws: Evidence From New York’S False Claims Acts, Yoojin Lee, Shaphan Ng, Terry Shevlin, Aruhn Venkat May 2025

The Deterrence Effects Of Tax Whistleblower Laws: Evidence From New York’S False Claims Acts, Yoojin Lee, Shaphan Ng, Terry Shevlin, Aruhn Venkat

Research Collection School Of Accountancy

In this study, we provide evidence on the effects of state tax whistleblower laws. We exploit a novel 2010 amendment to New York’s False Claims Acts (FCA) that explicitly extended whistleblower incentives to corporate income tax whistleblowers. We identify treated firms (firms exposed to New York’s FCA) using establishment-level data and descriptive analyses. Using a sample of firms exposed to New York and neighboring states, we find evidence that New York’s FCA reduced state tax avoidance. In cross-sectional tests, we find that effects are increasing in firms that grant fewer employee stock options and industry regulation, consistent with deterrence increasing …

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Monitoring Incentives And Tax Planning: Evidence From State-Owned Enterprises, Eva Eberhartinger, David M. P. Samuel May 2025

Monitoring Incentives And Tax Planning: Evidence From State-Owned Enterprises, Eva Eberhartinger, David M. P. Samuel

Research Collection School Of Accountancy

This study provides new evidence on the association of state ownership and tax planning by showing that a state owner’s monitoring incentives affect a firm’s tax planning. Using the setting of a developed market economy, Germany, we distinguish between state owners that directly benefit from state-owned enterprises’ (SOEs’) income tax payments and those that do not. Our results indicate that state ownership is not associated with less tax planning unless the state owner directly benefits from higher tax payments. These results are robust to various specifications and suggest that shareholders’ monitoring incentives are a determinant of a firm’s tax planning …

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Entangled Exclusions: Borders, Frontiers And Urban Geopolitics From Northeast India, Prerona Das, Gaurav Mittal, Jasnea Sarma May 2025

Entangled Exclusions: Borders, Frontiers And Urban Geopolitics From Northeast India, Prerona Das, Gaurav Mittal, Jasnea Sarma

Research Collection College of Integrative Studies

An epicentre of ethnicity-based identity politics and exclusions, India's northeastern region has long been politically imagined as both a ‘frontier’ and ‘borderland’ for state control, territorialization, extractive economies and (re)developments by colonial and subsequent post-colonial regimes. In post-independence India, the region experienced many territorial assertions made on ethnic grounds. With the rise of religio-national and neoliberal politics, new urban ‘developments’ and connectivity projects in the region have deepened exclusions based on class, caste, ethnic and religious borders. These have, in turn, led to further displacement, enclavization, and ghettoization of minority communities who are deemed ‘non-native’ along ethnocentric lines. Taking two …

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More Concerns About Atmospheric Methane Removal Efforts, Joshua Luczak May 2025

More Concerns About Atmospheric Methane Removal Efforts, Joshua Luczak

Research Collection College of Integrative Studies

The National Oceanic and Atmospheric Administration reported record-high global atmospheric carbon dioxide levels (419.3 ppm) in 2023, alongside atmospheric methane levels (1922.6 ppb) now over 160% above pre-industrial levels. The World Meteorological Organization predicts 2024 could surpass 2023 as the warmest year on record, with more frequent and severe extreme weather events. Meeting the Paris Climate goal of limiting global warming to well below 2°C—or ideally 1.5°C—above pre-industrial levels is becoming increasingly difficult. To address these challenges, efforts are expanding beyond reducing greenhouse gas emissions. While carbon dioxide removal (CDR) technologies have been the focus, attention is now turning to …

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Infrastructuring Planetary Rural Geographies: A View From China’S Rural Construction Movement, Ningning Chen, Lily Kong, Yurui Li May 2025

Infrastructuring Planetary Rural Geographies: A View From China’S Rural Construction Movement, Ningning Chen, Lily Kong, Yurui Li

Research Collection School of Social Sciences

This commentary responds to Wang et al.'s (2023) call for planetary rural geographies by attending to the neglected infrastructural dimensions. In so doing, we show how China's rural construction movement demonstrates Wang et al.'s (2023) three geographies of planetary rurality: as spaces of crisis, conflict, and hope. Simultaneously, we address how planetary rural thinking can foreground infrastructural geographies and their destabilization of urban-centered discourses, leading to a reconsideration of rural–urban relationality. We then identify new insights that critical infrastructural studies offer to planetary rural geographies. This includes an emphasis on the material grounds, hidden politics, and non-linear temporal patterns of …

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What Is Wrong With Workism?, Matthew Hammerton May 2025

What Is Wrong With Workism?, Matthew Hammerton

Research Collection School of Social Sciences

Workism is the phenomenon of people making their work the primary source of meaning and identity in their life. Recent critics of workism have argued that there is a growing trend towards it in many societies and that this is a bad thing. This article brings a philosophical perspective to the debate on workism. It develops a precise account of what workism is and evaluates the main objections raised against it by examining their underlying philosophical assumptions. Ultimately, it is argued that workism, as a way of life, is not as objectionable as its critics suggest.

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Dispositional Religiosity Predicts Increased Incidence Of Mixed Emotions: Evidence Across Five Studies Spanning Two Countries, Vincent Y. S. Oh, Andree Hartanto, Ringo M. H. Ho, Eddie M. W. Tong May 2025

Dispositional Religiosity Predicts Increased Incidence Of Mixed Emotions: Evidence Across Five Studies Spanning Two Countries, Vincent Y. S. Oh, Andree Hartanto, Ringo M. H. Ho, Eddie M. W. Tong

Research Collection School of Social Sciences

Across five studies (total N = 8,414), we examined whether religious individuals experienced more mixed emotions. Studies 1 and 2 examined associations between dispositional religiosity and mixed emotions, while Study 3 provided a pre-registered replication. Study 4 provided a pre-registered exploratory examination of three potential mediators of the relationship between dispositional religiosity and mixed emotions: trait dialecticism, cognitive reappraisal, and fear of God. Finally, Study 5 provided pre-registered prospective analyses testing associations between dispositional religiosity and mixed emotions 1 month later. Across all studies, positive and negative emotions were also examined, and latent variable structural equation modeling was performed, controlling …

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