Digital Commons Network^™

“Heavenly Fire Of The Godhead”: The Activity Of The Holy Spirit In The Macarian Writings, Daniel Wade Edwards

Dissertations (1934 -)

This dissertation addresses a lacuna within patristic scholarship on the doctrine of the Holy Spirit. Though the fourth century patristic writer known as “Macarius” addresses the theology of the Holy Spirit with unmatched depth and vibrancy, his pneumatological understanding has not yet been addressed adequately. Consequently, through a close literary analysis of the Spirit’s activity in the Macarian writings, this study proposes a threefold framework within which Macarius’ vision of the Spirit can be clearly perceived. In the first, the economic frame, the work of the Spirit within Old Testament Israel and the new covenant Church is compared and contrasted. …

Colonial Futures: Ngaio Marsh, War, And The End Of Empire, Heather M. Robinson

Publications and Research

Between the years of 1941 and 1945, Ngaio Marsh published three New Zealand-focused whodunnits; all three of these stories explore the impacts of the Second World War to some degree. What is curious is not that Marsh wrote about the war, but her sustained focus on New Zealand and New Zealanders, given that Marsh’s fiction usually took place in London or its surrounding counties. It marks the impact on Marsh of the global conflict that was changing the world, and shaking the foundations of colonialism and modernity as they had been known before 1939. In this essay, I explore how …

Automated Scoring Of Prosody In Oral Reading Fluency: Integrating Acoustic And Sentence/Chunk-Level Silence Features With Machine Learning, Kuo Wang

Education Policy and Leadership Theses and Dissertations

Prosody, the ability to read with appropriate variation in pitch, duration, pausing, and stress, is an important (and challenging to measure) dimension of oral reading fluency (ORF) and comprehension. ORF prosody is currently measured through human raters and rubric-based scoring systems (e.g., the National Assessment of Educational Progress (NAEP) or the Multidimensional Fluency Scale (MDFS scales). The rating process is labor and resource-intensive and introduces rater bias. Recent work has shown acoustic features to predict prosody ratings; however, their models had low generalization performance on cross-domain data (unseen passages and student samples).

The present study investigated the automated assessment of …

In The Shadow Of The Steeple: A Theory Of Religious Hypocrisy, Justin Arthur Rice

Graduate Theses and Dissertations

In this dissertation, I explore how Christian doctrine and practice respond to the pressures placed upon them by the troubling reality of religious hypocrisy (RH). Assuming a teleological notion of social institutions, I argue that RH is best understood in relation to the Church as an institution, and that RH occurs when religious agents undermine or subvert their appointed role within the Church. RH consists in the conscious or unconscious charade of spiritual or moral virtue undertaken in one’s capacity as a member of a religious institution, grounded in a fundamental disparity between one’s thoughts, words, desires, motivations, or deeds, …

Physics-Informed Machine Learning For Predictive Digital Twins In Greenhouses, Hoang Kim Tran

Graduate Theses and Dissertations

Greenhouses are widely used to create controlled environments for crop production, where indoor climate variables such as air temperature, relative humidity, CO2 concentration, radiation, and soil or substrate conditions directly affect plant growth, yield, energy consumption, and resource use. However, greenhouse climates are highly dynamic because they are influenced by complex interactions among outdoor weather, greenhouse structure, crop transpiration, heating systems, ventilation, screens, fans, irrigation, and other actuators. Building digital twins for greenhouses provides a powerful way to represent, monitor, and predict these climate dynamics. A predictive digital twin can simulate future indoor climate states based on current greenhouse conditions, …

Localizing And Repairing Backdoor-Sensitive Layers In Pre-Trained Language Models For Secure Fine-Tuning, Sunanda Das

Graduate Theses and Dissertations

Task-agnostic backdoor attacks can contaminate pre-trained language models (PLMs) in a way that survives downstream adaptation, even under full fine-tuning, making it difficult for practitioners to trust third-party checkpoints. Existing defenses often rely on privileged assumptions (e.g., access to poisoned data or trigger/target knowledge), thereby limiting their applicability in realistic settings. We present DiSec (Disentanglement of potentially adversarial weights for Secure fine-tuning), a robust and label-efficient purification framework that uses only clean auxiliary text and does not rely on downstream supervision or attack signatures. DiSec elicits model-internal signals from this clean data to separate suspicious parameter components that are inconsistent …

From Learner To Leader: Exploring Principals' Perspectives On Professional Learning, Development, And Mentoring, Eric William Kausch

Graduate Theses and Dissertations

This purpose of this qualitative study was to examine veteran secondary school principals’ engagement in professional learning, development, and mentoring for the improvement of their leadership skills. While previous literature provides insight into administrative preparation programs, mentoring of novice leaders, and succession planning for those advancing their careers, there are fewer studies that discuss enhancing experienced principals’ leadership development. The study was guided by three research questions: (1) How do principals describe their experiences participating in professional learning and development? (2) What types of leadership experiences do principals engage in to improve their leadership skills? and (3) How does engaging …

Drawing Conclusions: Autonomy And Mental Maps In Denmark And The Faroe Islands, Erik Steven Breidinger

Graduate Theses and Dissertations

This dissertation develops and tests a comparative heuristic device called optimal autonomy to explain when and how autonomous territories, or simply autonomies, become durable components of the global system of sovereign states. Drawing on a mixed‑methods case study of Denmark and the Faroe Islands, the study operationalizes optimal autonomy as a heuristic device using three interacting metrics: territorial delineation, national distinction, and state dependence. Using semi‑structured interviews with public officials and a mental‑mapping experiment with university students, this research shows that optimal autonomies are not made from single institutional designs but rather a dynamic equilibrium between maximal territorial delineation, medial …

A Dual Analysis Of Generic Stereotypes, Shaoneng Xu

Graduate Theses and Dissertations

In my thesis, I provide a dual-analysis on generic stereotypes, including a semantic analysis that focuses on the truth conditions of generic sentences as well as a pragmatic analysis that focuses on the normative force of generic stereotypes. The thesis contains two parts: In the first chapter, I make a semantic analysis of generic stereotypes based on Lemeire’s (2020) paper. I unpack the general concept of generic sentences and their truth-conditions. I also discuss Lemeire’s rebuttal strategies to offensive generic stereotypes, and add to it by indicating that generics can also carry normative forces. In the second chapter, I make …

Advancing Social Media Analytics And Personalized Generation Via Transfer Learning, Discourse-Aware Modeling, And Collaborative Modeling, Gibson Nkhata

Graduate Theses and Dissertations

Social media platforms have become central to information exchange, shaping public opinion across social, political, and economic domains. However, the massive volume of user-generated content, combined with its informal, nuanced, and often noisy nature, presents significant challenges for automated analysis and generation. Tasks such as stance detection, rumor verification, and personalized content generation are further complicated by sarcasm, evolving discourse structures, and diverse user preferences. Addressing these challenges requires models that can effectively leverage linguistic nuance, conversational dynamics, and collaborative user signals. Transfer learning has emerged as a powerful paradigm for improving performance in low-resource and complex language understanding tasks. …

Broadband Diffusion And Digital Preparedness In Tanzania: Harnessing The Role Of Technology In Formal Education, George Matto, John J. Iwata

Journal of Global Education and Research

Broadband, as a high-speed Internet connectivity, is an essential enabler for digital preparedness. However, little is known, in the case of Tanzania, about the nexus between broadband diffusion and digital preparedness, particularly in the facilitation of the teaching and learning process. This study, therefore, aimed at investigating the nexus between broadband diffusion and digital preparedness in Tanzania by focusing on the country’s readiness to leverage the same for formal education. The study employed a systematic review, guided by the PRISMA framework, to obtain the empirical evidence from existing literature. Thematic analysis was used to identify themes, analyze, and interpret qualitative …

Sjsu Erfa News, Summer 2026, San Jose State University, Emeritus And Retired Faculty Association

Emeritus and Retired Faculty Association (ERFA) Newsletter

Volume 39, No 39

Medadl: High-Throughput Information Extraction Of Functional Status From Electronic Health Records To Advance Frailty Assessment In Older Adults, Sunyang Fu, Zhiyi Yue, Jennyly T Nguyen, Huipeng Liu, Jaerong Ahn, Vanessa Ramirez, Jude Des Bordes, Hongfang Liu, Min Ji Kwak, Nahid J Rianon

Faculty, Staff and Student Publications

Background: Functional status is essential for assessing frailty and planning care in older adults but is often under-documented in the structured fields of electronic health records. Manual chart review can capture functional status information but is labor-intensive and time-consuming. In this study, we developed and validated a scalable natural language processing (NLP) model to extract functional status information from unstructured electronic health record (EHR) notes.

Methods: This retrospective cohort study included 110 older adults seen at a geriatric osteoporosis clinic. A large language model-augmented symbolic NLP pipeline (MedADL) was developed to extract activities of daily living (ADL) and instrumental activities …

Implementation Brief 2 Actionable Foundational Practices Tool, Center On English Language Proficiency

Resources

No abstract provided.

Implementation Brief 2 El State Policy Brightspots, Center On English Language Proficiency

Resources

No abstract provided.

A Student’S Confidence And A Teacher’S Practice: Reflecting On Parallel Writing Journeys In A Theatre-Making Classroom In South Africa, Néka Da Costa

GHEA21 Publications

No abstract provided.

Slowing The Academic Treadmill: Writing, Reflection, And Resistance In The Neoliberal University, Birsha Ohdedar

GHEA21 Publications

No abstract provided.

Highly Confident But Slightly Uncertain: A Long Overdue Reinvention Of The School Scientific Method, Uncertainty And Error - Volume 3, Stephen Demeo

Publications and Research

Volume 3 explores the essential roles of uncertainty and error in scientific experimentation. It distinguishes between scientific error and scientific uncertainty: Scientific error refers to the difference between an experimental value and an accepted literature value, as well as the difference between data points in an x-y scatter plot and a predicted trendline. Scientific uncertainty, on the other hand, is associated with doubt arising from instrument limitations, variability within a data set, and psychological factors. Human error is set apart as mistakes or blunders, not to be conflated with scientific error.

Of utmost importance to the scientific investigator is the …

Impartial Intelligence? Evidence Of Country-Label Sensitivity In Ai Financial Analysis, Fabio Motoki, Jedson Pinto

School of Accountancy Faculty Publications

This study examines whether large language models exhibit systematic country-contingent differential treatment in financial fraud detection. Analyzing 30,000 synthetic transactions with identical statistical properties across three country attributions (United States, Great Britain, and China), we find LLMs assign significantly higher fraud probabilities to Chinese-attributed transactions (36.2%) compared to Western countries (≈30–31%), resulting in accuracy disparities of 67% versus 74%. The gap remains stable across five independent experimental replications and persists when using Chinese language prompts, ruling out linguistic effects. Bias mitigation strategies, such as requiring explanations or explicit country neutrality instructions, reduce but fail to eliminate these disparities. Testing across …

Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma

Research Collection School Of Computing and Information Systems

Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic uncertainty of real-world events. To bridge this gap, we advance open-ended event forecasting from pinpoint forecasting to scatter forecasting by introducing the proxy task of hypothesis generation. This paradigm aims to generate an inclusive and diverse set of hypotheses that broadly cover the space of plausible future events. To this end, we propose SCATTER, a reinforcement learning framework that jointly optimizes inclusiveness and diversity of the hypothesis. Specifically, we design a novel hybrid reward that consists of …

Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang

Research Collection School Of Computing and Information Systems

Document Question Answering (DQA) involves generating answers from a document based on a user’s query, representing a key task in document understanding. This task requires interpreting visual layouts, which has prompted recent studies to adopt multimodal Retrieval-Augmented Generation (RAG) that processes page images for answer generation. However, in multimodal RAG, visual DQA struggles to utilize a large number of images effectively, as the retrieval stage often retains only a few candidate pages (e.g., Top-4), causing informative but less visually salient content to be overlooked in favor of common yet low-information pages. To address this issue, we propose a Multi-Armed Bandit–based …

The Narrative Dynamics Of Special Books By Special Kids Youtube Videos And Comments: A Study Of Disability Rhetoric And Public Narrative Engagement, Jessica Louise Allee

Graduate Theses and Dissertations

Digital media has expanded disability advocacy and community building by enabling accessible, visual storytelling and connection. Special Books by Special Kids (SBSK), a YouTube channel using interview-based disability storytelling, foregrounds people’s experiences with disabilities in the videos, while inviting viewers to interpret, identify with, and respond in the comments. As a participatory storytelling space, SBSK offers a site for examining how disability meanings are constructed, negotiated, and transformed through narratives, multimodal practices, and audience uptake, while revealing how dominant disability rhetoric or ableist discourse that positions people with disabilities as burdens, inherently deficient, or socially devalued, can be reproduced, complicated, …

Purifai: Detecting And Fixing Search-Induced Distortions In Web-Augmented Llms, Guoqing Wang, Zhao Zhang, Zeyu Sun, Xiaofei Xie, Yizhou Chen, Yanchao Tan, Dan Hao

Research Collection School Of Computing and Information Systems

As Large Language Models (LLMs) increasingly serve as interfaces for proprietary data (e.g., enterprise knowledge bases, legal statutes), ensuring their fidelity to trusted internal information is paramount. While integrating real-time web search can enhance model utility, it introduces a critical vulnerability: the ingestion of conflicting, misleading, or hallucinated content from the open web can override the model's adherence to its verified internal knowledge. We define this failure mode as search-induced distortion, a significant risk in high-stakes domains where the internal knowledge base serves as the absolute ground truth.To address this challenge, we present PurifAI, a proactive, model-agnostic, cache-level purification system …

Verbalizing Lightgcn: Direct Learning Of Textual Representations From User-Item Interaction Graph Via Llms, Manh-Khanh Ngo Huu, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In this work, we propose VerbaLightGCN, a novel LLM-based recommendation framework that integrates the semantic understanding of LLMs with user-item interaction modeling. Traditional collaborative filtering (CF) models typically embed user and item IDs into a latent space to capture interaction signals. However, pretrained LLMs cannot natively interpret these learned embeddings. To bridge this gap, VerbaLightGCN adopts a CF-as-text paradigm, in which collaborative signals are encoded in textual form and directly learned from the user–item interaction graph, and are then combined with semantic information to construct user and item profiles that function as latent embeddings. Inspired by LightGCN, our method retains …

Managing Risks Under Nuclear Power Plant Projects: A Latent Similarity-Guided Contract Customization, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Global energy is transforming, with nuclear power emerging as a pivotal player in achieving sustainable and low-carbon energy goals. The nature of nuclear technology introduces unique challenges, such as stringent safety and environmental requirements. Existing studies focus on general risk identification, such as supply chain delays, cost overruns, and public perception issues. However, these studies fail to address integrating these risks into tailored contractual provisions, which are critical for navigating the unique challenges of nuclear projects. The goal of this paper is to examine how standard construction contracts can be tailored to better accommodate the risks inherent in nuclear power …

Rhetorical Physics And The Laws Of Language: A Comparative Analysis Of President Trump And President Macron At The United Nations 2025, David Edmund Allen

Research outputs 2022 to 2026

The paper features a textual analysis of the UN speeches made by the US President Donald Trump and by France’s President Macron. President Trump’s speech was made in the absence of a teleprompter and lasted almost an hour. President Macron’s speech was representative of a more standard diplomatic speech. Both speeches are analyzed using a variety of models and techniques. The analysis incorporates an exploration of Manin’s link of Zipf’s law to concepts from information theory and algorithmic complexity, Tao’s concepts applied to power laws, ‘E pluribus unum’, out of many, one, plus a completely new application of Villermaux’s universal …

Do I Fit In Here? How Immigrants’ Endorsement Of Social Markers Is Related To Their Wellbeing In Three Migrant Receiving Societies, Justine Dandy, Chan Hoong Leong, Adam Komisarof, Travis Lim, Krystal Perkins

Research outputs 2022 to 2026

Social markers of acceptance are the attributes seen as important for immigrants to achieve or display in order to be accepted similarly to a local-born citizen. In research on constructions of national identity, factor analysis reveals a culture-specific, two-factor structure akin to the ethnic–civic distinction observed. In this paper, we extend this work by examining the relationship between social markers of acceptance and immigrants’ well-being in three national contexts: Australia, Japan, and the U.S. Specifically, in study 1 we examined the factor structure of social markers in non-immigrant samples in each context (Australia, n = 1357; Japan, n = 2000; …

Variational Speculative Decoding: Rethinking Draft Training From Token Likelihood To Sequence Acceptance, Xiandong Zou, Jianshu Li, Jing Huang, Pan Zhou

Research Collection School Of Computing and Information Systems

Speculative decoding accelerates inference for (M)LLMs, yet a training-decoding discrepancy persists: while existing methods optimize single greedy trajectories, decoding involves verifying and ranking multiple sampled draft paths. We propose Variational Speculative Decoding (VSD), formulating draft training as variational inference over latent proposals (draft paths). VSD maximizes the marginal probability of target-model acceptance, yielding an ELBO that promotes high-quality latent proposals while minimizing divergence from the target distribution. To enhance quality and reduce variance, we incorporate a path-level utility and optimize via an Expectation-Maximization procedure. The E-step draws MCMC samples from an oracle-filtered posterior, while the M-step maximizes weighted likelihood using …

Itimo: An Llm-Empowered Synthesis Dataset For Travel Itinerary Modification, Zhuoxuan Huang, Yunshan Ma, Hongyu Zhang, Hua Ma, Zhu Sun

Research Collection School Of Computing and Information Systems

Addressing itinerary modification is crucial for enhancing the travel experience as it is a frequent requirement during traveling. However, existing research mainly focuses on fixed itinerary planning, leaving modification underexplored due to the scarcity of shape need-to-modify itinerary data. To bridge this gap, we formally define the itinerary modification task and propose a general pipeline to construct the corresponding dataset, namely iTIMO. This pipeline frames the generation of shape need-to-modify itinerary data as an intent-driven perturbation task. It instructs large language models to perturb real-world itineraries using three operations: REPLACE, ADD, and DELETE. Each perturbation is grounded in three intents: …

Evaluating Special Education Teachers’ Competence In Inclusive Education: A Study Of Behavior Management, Level Of Confidence, And Training Needs, Kourtney Guthrie

Electronic Theses and Dissertations

The purpose of this mixed-methods study is to examine the competence of special education teachers in rural East Texas, focusing on their experiences, perceptions, and professional development needs related to behavior management and inclusive education. Quantitative data were gathered through questionnaires given to special education teachers and elaborated upon through focus group interviews, where themes emerged. An explanatory sequential mixed-methods design was used to develop a better understanding of teachers’ preparedness and the problems involved in the implementation of inclusive practices. The findings may inform more effective teacher training, policy-making, and support systems in rural educational settings by highlighting professional …