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Applying a Systems Psychodynamics Lens to Examine Group Processes Influencing Organizational Readiness for Change: A Mixed-Methods Approach
No full textAlthough current change literature is replete with prescriptive models on how to effectively implement organizational change, empirical evidence indicates that the success rate of organizational change continues to be low. Additionally, while several researchers argue that understanding both overt and covert dynamics in groups and teams is crucial for successfully navigating organizational change, research on the role of covert group processes in OCR is limited. The first goal of this comprehensive research was to address this gap in the literature by using an evidence-based approach to examine the role of both overt and covert group processes in developing organizational change readiness (OCR).
This paper used a systems psychodynamics approach to explore the system, i.e., the structural aspects of the organizational change, as well as the psychoanalytic perspectives within that system, such as individual experiences, affective responses to change, and conscious and unconscious group processes pertaining to change. Affect was assessed in three ways – by incorporating visual research methods such as images to access change-related affect and unconscious implicit dynamics, through an affect scale, and via interviews. The second goal of this research was to explore the use of a mixed-methods multiple-case design to collect and analyze data to leverage the strengths of both quantitative and qualitative methods and enable cross-case comparisons to gain a deeper, more nuanced understanding of the topic.
The research findings demonstrated that employees’ affective responses to change significantly influenced OCR in both groups. Specifically, the results revealed a statistically significant difference in affect between the two groups as well as significant associations between affect and the change readiness measures of need for change, leadership alignment, and vision for change in both groups. Furthermore, the mixed-methods analysis uncovered the prevalence of covert subgroup dynamics and sources of resistance that likely influenced affect and change efforts in both groups. Finally, the multiple-case design used in this research elucidated the importance of considering contextual and within-group factors such as organizational culture, change history, industry, and employee demographics in developing change readiness.
These findings emphasize the need for organizations to incorporate examining employees’ affective response to change as an integral part of their assessment of change readiness. Moreover, it is critical for organizations to utilize both quantitative and qualitative methods to collect data to gain valuable insights into both overt and covert group processes prevalent at the intergroup, intragroup, and organizational levels, and evaluate their potential impact on developing OCR
Three Essays on Health Inequality: Probing Entanglements of Health Inequality as Strengthening Coloniality and the Developmental Piloting of a Novel Psychological Intervention and Iterative Artificial Intelligence Model
No full textThis dissertation encompasses three papers exploring health inequality. Paper one explores theoretical and methodological literature on health inequality. Paper two utilizes scholarly scaffolding considered in paper one to present an empirically supported novel health education program curriculum as sutured to a novel psychotherapeutic approach. Paper three discusses the theoretical, technical, scholarly and feasibility dimensions of integrating the novel health education curriculum into an artificial intelligence (AI) natural language machine learning language model and (NLML) mobile health application
Authenticity and Leadership in Context: Exploring Senior Executives’ Perceptions of Self and Authenticity in Financial Organizations
No full textThe purpose of this study was to explore senior executives’ perceptions and experiences regarding authenticity and authentic leadership within the financial sector.
This research examined how 12 senior executives in the financial industry described their authentic selves, defined being authentic at work, practiced their authentic leadership, and learned to lead authentically in a high-pressure industry. Eleven followers of three senior executives also participated through the Authentic Leadership Questionnaire (ALQ) and qualitative survey questions, providing a more nuanced understanding of authentic leadership. Data collected through semi-structured interviews and the ALQ revealed that executives practiced a form of “bounded authenticity”—strategically calibrating self-expression within professional parameters rather than engaging in unrestricted self-disclosure.
The study identified five key findings: (1) authenticity in finance manifested as contextually negotiated rather than absolute; (2) authentic leadership is inherently relational in nature; (3) thoughtful emotional regulation and composure, rather than unfiltered emotional transparency, were valued as authentic leadership; (4) industry culture significantly constrained the expression of authenticity; and (5) the development of authentic leadership occurred primarily through experience, reflection, and relationships, rather than formal training programs.
The findings challenged universal models of authentic leadership by demonstrating the significant impact of the financial industry context on how authenticity is expressed in competitive environments, highlighting the importance of awareness, relationship-building capabilities, emotional awareness and groundedness, and an experiential learning mindset that integrated self-development with leadership skills
E tetele a Pesega ae matua i le Oo: Living with Climate Change in Apia, Samoa
No full textThis case study explores the lived realities of climate change in Samoa’s capital region. The Apia Urban Area (AUA), home to a significant portion of Samoa’s population and infrastructure, faces increasing environmental risks due to rising temperatures, more intense rainfall, flooding, and sea level rise. The study highlights the multifaceted strategies employed by Samoans to adapt, including household mobility, infrastructural developments, and community-based conservation initiatives. Key projects such as the Apia Waterfront Development Project and the Vaisigano Catchment Project demonstrate integrated approaches to urban climate resilience that combine traditional knowledge, modern planning, and external funding. The findings underscore the importance of inclusive, culturally grounded, and adaptive responses to climate change that align with local needs and practices, ensuring sustainable urban resilience in Samoa’s most vulnerable areas
Soil N₂O Emissions in Organic Farming Systems: A North American Meta-Dataset
No full textAccurately quantifying nitrous oxide (N₂O) fluxes is critical for improving nitrogen management in agriculture. While numerous studies, reviews, and datasets have examined N₂O emissions in conventional farming systems, there remains a lack of comprehensive data focused specifically on organic systems in North America. This work addresses that gap by compiling N₂O emission data from 43 peer-reviewed studies conducted in organic farming contexts across North America. It includes detailed information on organic nitrogen amendments, area- and yield-scaled N₂O emissions, emission factors, flux ranges, and key agronomic and environmental variables such as crop type, management practices, and climate conditions. A meta-analysis based on this dataset will support improved management strategies and evidence-based policymaking
Fatma Begum
No full textAs India’s first known female director and producer, Fatma Begum’s career was a bold challenge to the prevailing norms of her time, making her one of the most groundbreaking figures in Indian cinema. During her impactful career, which spanned from 1922 to 1937, she also worked as a film actress and screenwriter and owned her own production company called Fatma Film Company, later renamed Victoria Fatma Film Company. As a Muslim woman, her contributions to early Indian cinema also challenge dominant historiographical narratives that have traditionally focused on Hindu mythological and devotional films made primarily by upper caste Hindu males. Having been involved in over twenty films during the silent era, none of which are considered extant today, Begum thus stands as a significant yet spectral figure in the history of Indian cinema
Fixed dosing versus weight-based dosing of HIV-1 prophylactic monoclonal antibodies in adults: a post-hoc, cross-protocol pharmacokinetics modelling study
No full textFor HIV-1 prophylactic mAbs, a fixed-dose approach, possibly banded by weight categories may be advantageous over weight-based dosing, as it offers increased operational efficiency while maintaining comparable pharmacokinetics and inter-individual consistency.
Keywords: HIV prevention; Dosing strategy; Exponent of body weight; Two-compartment; Population pharmacokinetics model; Variability in exposur
Probing polarity structure–function relationships in amine–water mixtures
No full textThis study investigates the relationships between chemical structure, polarity, and miscibility in solvent–water systems to elucidate the mechanisms underlying the thermoresponsive hydrophilicity of amines. By integrating complementary analyses of Kamlet–Taft parameters and relative permittivity,we reveal that hydrogen bonding and nanoscale ordering, i.e., molecular-level and mean-field, respectively, underlie amine–water interactions, which, in turn, influence the thermomorphic hydrophilicity
Exploration for Equivalent Access to Interactive Digital Media
No full textDigital media plays a significant role in our everyday lives, from education and work to entertainment and social interactions. Yet, with its increasing pervasiveness comes the added responsibility to ensure it is open and accessible to all. While there have been strides in making various forms of digital media accessible, the extent to which this access is truly equivalent is still questionable. For instance, the experiences of blind and low vision (BLV) users within various forms of media are heavily simplified, and their experiences are rarely comparable to that of their sighted counterparts. This raises a critical question: How can we provide more equivalent access to digital media?
This dissertation proposes facilitating exploration as a way to achieve more equivalent accessibility. By giving users the ability to freely experience spaces and media without excessive guidance and simplification, we can grant them a heightened sense of agency and fulfillment. Through this, we make accessibility not just about access to information but also about access to meaningful experiences.
I focus on BLV users' experiences within two forms of media: 3D video games and digital images. Within these contexts, I explore various techniques for facilitating exploration — designing tools, evaluating them with BLV users, and comparing them against existing tools to understand how exploration affects users' experiences. First, I present NavStick, a tool that enables self-directed information scanning, allowing BLV players to "look around" their immediate surroundings within a 3D game world. Second, I evaluate a range of spatial awareness tools (including NavStick) to assess how multimodal and complementary representations of information can promote environmental awareness for BLV players. Third, I introduce Surveyor, an in-game exploration assistance tool that scaffolds the exploration process in order to enhance discovery in BLV players. Finally, I present ImageAssist, a suite of tools that streamline the exploration of digital images through targeted scaffolding, helping users to more efficiently survey an image via touch on a touchscreen.
Across dozens of user study sessions, I found that when BLV users could explore more freely (rather than being limited to simplistic or guided interactions), they report a stronger sense of agency, a better understanding of the media, and more meaningful experiences. These tools supported users' core psychological needs — such as autonomy, competence, and learning — and consistently led to greater fulfillment and engagement. This dissertation shows how building interfaces around exploration can improve user experience, highlighting the importance of supporting exploration in interactive systems
Reducing Label Dependence in Animal Behavior Modeling: Diverse Supervision Strategies for Improved Generalization
No full textUnderstanding and modeling animal behavior is a central goal in behavioral neuroscience and computational ethology. With advances in imaging and tracking technologies, the field hasentered a new era of high-dimensional spatiotemporal data. However, the ability to provide high-quality labels has not—and inherently cannot—scale at the same pace. This growing gap underscores the need for diverse forms of supervision to extract meaningful insights from increasingly complex behavioral datasets.
This dissertation presents a series of computational frameworks for representing and segmenting animal behavior, progressing from pose estimation to structured temporal modeling, with a focus on leveraging supervised, semi-supervised, and unsupervised methods.
The first part of this dissertation focuses on semi-supervised keypoint estimation in multi-animal settings. In Chapter 2, we introduce SemiMultiPose, a semi-supervised model for multi-animal pose estimation that combines supervised keypoint annotations with unsupervised losses on unlabeled video data. By leveraging the structure inherent in pose-based representations, this framework extracts meaningful intermediate features from raw video, even in the absence of dense labels. This approach enables reduced supervision requirements and improved generalization in complex behavioral settings, demonstrating the value of incorporating unlabeled frames into the training process.
Chapter 3 presents a comparative analysis of action segmentation frameworks under different supervision regimes. Action segmentation involves classifying discrete animal behaviors over time based on spatiotemporal features extracted from video. We evaluate supervised, unsupervised, and semi-supervised methods on multiple benchmark datasets, highlighting their trade-offs in performance, data efficiency, and interpretability. This study underscores the importance of temporal structure and representation learning in developing scalable, accurate models of behavior.
The third part of the dissertation, presented in Chapter 4, focuses on transformer-based behavior segmentation. We adapt vision transformers (ViTs) for behavioral video analysis by first extracting unsupervised frame-level representations from raw video using a pretrained ViT backbone. These embeddings are then used as inputs for action segmentation models, leveraging the temporal modeling tools developed in Chapter 3. We also explore combining these video-derived features with structured pose representations to improve segmentation performance. This work, part of a collaborative project, demonstrates the effectiveness of ViT backbones in segmenting behavior from both raw video and pose data.
Chapter 5 turns to the problem of encoding behavior into neural activity. Building on the representations developed in earlier chapters—continuous kinematic features from Chapter 2 and discrete behavioral states from Chapter 3—we examine how these different forms of behavioral abstraction are reflected in neural population activity. We develop and evaluate encoder models that map these distinct behavioral representations into neural space, with a focus on how the structure of the input—symbolic versus metric—shapes the geometry, predictability, and biological interpretability of the resulting neural codes.
Together, these chapters address the central challenge of extracting meaningful insights from large volumes of high-dimensional spatiotemporal data. By developing behavior modeling methods under varying levels of supervision, this work shows how structured representations can emerge even when labeled data are limited. Finally, neural encoding models provide a framework for probing how these learned representations—both continuous and discrete—are reflected in neural activity, offering a principled lens into the brain-behavior relationship