Master of Science, The Ohio State University, 2022, Industrial and Systems Engineering

Decades of cognitive systems engineering research has revealed that implementing human-machine teams into complex environments can consequently result in challenges that negatively impact human-machine teams. Such challenges and conflicts amongst team members can readily be observed in human-machine teams where agents are assigned heterogeneous tasks because the agents' individual goals may have a tendency to conflict and compete with one another in their shared environment. This conflict may also be magnified if the agents of our heterogeneously tasked human-machine team do not share a common goal and are not equipped with the resources to manage their differences. In our study, we set out to determine how the performance of our heterogeneously tasked agents in our simulated human-machine team was impacted in our full-motion video and intelligence analysis. By using joint-performance activity graphs, various statistical analyses, constant comparative analysis, and human-machine teaming heuristic analysis, we were able to determine that the performance of our human-machine team was not significantly different from the performance of our participants who worked alone. This led us to the conclusion that the machine agent insufficiently aided their human agent's decision making during the full motion video analysis and the design of the machine failed to adhere to known Human-Machine Teaming heuristics. Lastly, this holistic analysis revealed that the machine agent acted as if it did not have any knowledge of the ultimate goal of their human agent, and due to its limited capabilities, the machine was unable to contribute information in relation to the overarching goal. Even though the architecture of the human-machine team in this study failed to adhere to various human-machine teaming heuristics, failing to adhere to and implement the team so that both the agents' individual tasks meaningfully contributed the shared goal was determined to be the most criti (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 0, Systems Biology and Bioinformatics

Mouse models of Alzheimer's Disease (AD) show progression through stages reflective of human pathology. Omics identification of temporal and sex-linked factors driving AD related pathways can be used to dissect initiating and propagating events of AD stages to develop biomarkers or design interventions. In this dissertation, we conducted label-free proteome and phosphoproteome measurements of mouse hippocampus tissue with variables of time (three, six, and nine months), genetic background (5XFAD vs. WT), and sex (equal males and females). These time points are associated with well-defined phenotypes with respect to: Aβ42 plaque deposition, memory deficits, and neuronal loss, allowing correlation of proteome based molecular signatures with the mouse model stages. I identified twenty-three novel AD-related proteins, six of which are differentially expressed between male and female 5XFAD. At a pathway level the 5XFAD specific upregulated proteins are significantly enriched for DNA damage and stress-induced senescence at 3-months only, while at 6-months the AD-specific proteome signature is altered and significantly enriched for membrane trafficking and vesicle-mediated transport protein annotations. By 9-months AD-specific dysregulation is also characterized by significant neuro- inflammation with innate immune system, platelet activation and hyper- reactive astrocyte related enrichments. Complementing these findings, the phosphoproteome is also marked by early DNA damage control (including cell survival and mRNA regulation signatures), however at six months these signatures are substituted by striking disruption of synaptic signalling and cell cycle regulation. Lastly, global MSOx profiling exposed the connection between increased Met(O) peptides and the selective downregulation of antioxidant defenses. This dissertation offers a novel systems-based understanding of AD dynamics, our multi-layered characterization of translational and post- translational pathways (open full item for complete abstract)

Master of Science, The Ohio State University, 2022, Environment and Natural Resources

Complex interactions among biophysical and social systems present challenges for environmental problem-solving. Addressing climate change is a prime example. Climate change can be described as a systems problem characterized by a highly interconnected system structure that produces undesirable outcomes. This complexity highlights the importance of employing systems thinking. Systems thinking departs from the traditional approach of breaking down a system into its separate components, and instead accounts for the complex and dynamic interactions between them, enabling the evaluation of outcomes of decisions and interventions at multiple scales. Accordingly, higher educational institutions are increasingly incorporating systems thinking in their curriculum and pedagogy to produce a qualified cadre of systems thinkers capable of addressing the complex problems they will encounter in their careers. More specifically, systems thinking has been identified as a fundamental element of environmental education as it trains students to integrate information across multiple scales, allowing them to develop effective solutions for today's multidimensional environmental challenges. However, there are still significant knowledge gaps on how to promote and assess systems thinking in formal educational settings. This thesis contributes to the literature in several ways. In chapter two, I apply a systems approach to identify network-derived indicators of systems thinking by analyzing 35 cognitive maps of university students. The key contribution of this work is the development of a novel conceptual framework that integrates three fundamental dimensions of systems thinking – system components, system structure, and system function. Using hierarchical clustering, I identify and distinguish between simple versus complex systems thinking based on how cognitive maps with similar results cluster together. Subsequently in chapter three, I examine how different factors pertaining to a stude (open full item for complete abstract)

Master of Science, The Ohio State University, 2022, Industrial and Systems Engineering

Human societies are themselves tangled layered networks of human, biological, and technological systems. In the last decade alone, these networks have experienced massive shock events in the form of natural disasters, infrastructure failures, and pandemics. These events will only continue and will likely include unexpected new forms of shocks in the future. Researchers across disparate disciplines have recently begun to investigate resilience in society, and how our built systems contribute to or degrade it, but there has not yet been an attempt to field a system informed by resilience research in a relevant real-world setting. This paper describes an effort to bolster the capabilities of public health work by using resilience engineering principles to generate a new extra-organizational capability amid the COVID-19 pandemic. This new capability attempts to engage the public as a part of a societal scale team engaged in a joint activity to identify positive COVID-19 cases. Our work reveals insights about is required to generate new non-standard capabilities for the benefit of society. These, in turn, reveal some of the dynamics of a society enduring a critical disruption, which future work into societal resilience will need to consider to be successful.

Master of Science in Biomedical Sciences (MSBS), University of Toledo, 2022, Biomedical Sciences (Bioinformatics and Proteomics/Genomics)

Cortical function comprises the gestalt of sensory processing mechanisms in the brain giving rise to higher-order perception, cognition, and behavior that underlies consciousness. However, traditional feed-forward theories of neuroscience fail to capture the complexity of functional interactions within the neural connectome leading to these phenomena. Prevailing theory is now positing a predictive processing framework to better describe the architecture of the cortex. C. elegans permits high-content behavioral phenomics and recording of wholebrain activity across all 302 neurons simultaneously. As such, C. elegans presents a tractable model to connect behavior to neurobiology and to test the assumptions of cortical theory. To that end, we performed whole-brain imaging in tandem with phenomic fingerprinting of behaving C. elegans in response to both aversive stimuli eliciting backwards locomotion and food-like stimuli eliciting attraction. Calcium imaging profiles revealed highly dynamic neurons with activity patterns wherein a feed-forward model does not fully explain neuronal nor behavioral response to stimuli. Suggestive of a complex sensory integration, we sought to apply a datadriven systems approach to characterize these nonlinear interactions and assess the complexity of the functional connectome in C. elegans. Ultimately, we suggest a loci for a novel correlate of the predictive processing framework emerging as a distributed computation of the neuronal network after stimulus-dependent rewiring of functional circuitry, posing an avenue for further study. As schizophrenia, autism, major depression, Alzheimer's disease, and age-related cognitive decline are linked to impairments in sensorimotor processing, this work represents an important step forward in advancing our understanding of the cortex and pathophysiology of neuropsychiatric disease.

Master of Engineering, Case Western Reserve University, 2022, EECS - System and Control Engineering

Quadcopter, also known as a drone, rotorcraft, or quadrotor, is a small-scale UAV used for various applications like photography, inspection, etc. Its composition contains two parts: reliable hardware and an effective control algorithm. To maximize its performance, developing a reliable control algorithm is essential. Also, while the quadcopter is facing the propellers failure, a proper solution for maintaining its stability is necessary. In this thesis, the proposed controller is designed based on Lyapunov analysis using a nested saturation algorithm. First, the dynamic model of the four-rotor quadcopter is obtained via a Lagrange approach. Then the proposed controller is designed, and a global stability analysis of the closed-loop system is presented. Next, the MATLAB simulations show that the controller can autonomously perform flying experiments of taking off and hovering. In the second part, the periodic solutions and equilibria for the situations that quadcopter lost one and two (opposing) propellers are introduced.

Doctor of Business Administration (D.B.A.), Franklin University, 2022, Business Administration

The purpose of this mixed methods study was to determine how entrepreneurs who start new businesses can mitigate business decision risk while exploring how their business experience plays a role in their decision-making process. Previous meta-analysis of Ultimatum Game bargaining has shown that student populations do not follow a Nash Equilibrium. Based on a review of literature, the author's study explored if entrepreneurs would make offers closer to the Nash Equilibrium, (risker) based on their business background. While entrepreneurs did not make statistically different offers than the student group, their unique background and experiences did play a significant role in how they approached the problem with several significant findings: 1) Entrepreneurs ($4.76, average offer) did not make different (p = .805) offers than those of the students ($4.86 average offer). 2) There was not a significant difference (p = 0.846) between the acceptance rates of the entrepreneurs (88%) and the students (91%). 3) There was a significant difference (p = <0.001) between how entrepreneurs (3.85 on a Likert scale) viewed their background's role in decision making, and that of the student group (2.90). 4) There was a significant (p=0.017) medium negative correlation (-0.348) between entrepreneurs' feelings of risk and the size of their offer amounts. The qualitative results found that the decision making of the entrepreneurs was influenced by key themes of: Responsible Risk Taking, A Sense of Fairness, Altruistic Outlook, Application of Business Experience, and A Nash Mindset.

Doctor of Philosophy, Case Western Reserve University, 2022, Systems Biology and Bioinformatics

The evolution of therapeutic resistance in cancer is a complex and nearly inescapable process driven by evolutionary dynamics. As the genomic characterization of cancer has provided insight into the mechanisms of oncogenesis, tumor growth, and metastasis we have developed targeted therapeutics to provide personalized treatment based on mutation status. Yet, most cancer patients are not helped by these drugs, with just over 7\% of cancer patients in the United States benefiting from genome-driven care in 2020. In this work, we propose that an evolutionary-driven problem requires an evolutionary-inspired solution. We present a novel method for extracting therapeutic response biomarkers in cancer, and demonstrate its utility in large, publicly-available datasets, tightly-controlled in silico experiments, and translational efforts. Our procedure exploits principles of convergent evolution to find patterns across tumors with distinct evolutionary histories and mutational profiles. First, we use this signature extraction method to predict collateral treatment response in Ewing's sarcoma cell lines. While evolving resistance to standard of care treatment across multiple evolutionary replicates of a Ewing's sarcoma cell line, we compared gene expression between responders and non-responders to a variety of second-line treatments. Differential gene expression results were compiled to generate biomarkers of therapeutic response which are hypothesized to be clinically relevant, but require further validation. Next, we use epithelial cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) database to extract the Cisplatin Response Signature (CisSig). CisSig is predictive of cisplatin IC50 in GDSC cell lines, clinical trends in tumor sample databases, and survival outcomes in patients who received cisplatin-containing chemotherapy. Finally, we propose translational efforts to move two gene expression signatures, CisSig and the genome-adjusted radiation dose (GARD), (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2021, Communication Studies (Communication)

This dissertation is interested in affect, or the aspects of social life that make a difference because of the ways we feel them. The happenings of a group working in public health are interpreted using affect theory to trace how disruptions to typical organizing processes happen. Because of its role in shaping social scenes, understanding affect's operation is a potential route towards change, even in situations that seem to be solidly set in one particular form. Instances of the group reworking understandings of their role in addressing health equity and disparities are presented to highlight affect's operations--a force that can lead to positive, negative, or ambiguous change. Feminism informs this research both theoretically and in its commitments to considering the practical implications of learning from this group. Feminist formations of affect are foregrounded by thinking about how bodies are involved in sensing the world as well as the role of love and support in the collectivities of our organizing efforts. The affective movements of the group are traced by sensing the trajectories of the way things are heading, identifying patterns, and accounting for power's role. Implications for communication and organizing in public health theory and practice are offered, calling for public health to engage affective analysis by developing capacities for self, group, and structural reflection on the sociocultural underpinnings of population health.

Ph.D., Antioch University, 2021, Leadership and Change

The purpose of this study is to better understand how to influence capitalist attitudes and drive more capital towards social good. This is why we must explore the prospect of emancipating the capitalists from capitalism. This study identifies capitalism as a form of oppression that is contributing to a newly developed ethics of capital, a term introduced in this study. Emancipatory action research and general systems theory were employed as the primary approaches to engaging a group of venture capitalists and finance professionals in activities and dialogues. Value2 is the theory of action I use to influence the attitudes of the participants in the study. I developed the Emancipatory Action Map as a tool for capturing the epistemological process catalyzed by Value2. The findings identified common themes and contrasts, such as how participants rationalized their problem-solving, how they responded to the isomorphism between systems operating within capitalism, and how they experienced their own agency in relationship to the problem of driving more capital towards social good. This dissertation is available in open access at AURA, https://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.edu/etd.

Doctor of Philosophy, University of Akron, 2021, Engineering

Lean Management Systems (LMS) and Continuous Improvement (CI) program deployments are increasingly becoming an important strategy for many organizations for gaining competitive advantage. Such deployments promise success to organizations of any nature and size. Significant resources in the form of employee time, external consultants and training programs are spent on LMS/CI deployments by a vast number of companies every year. Yet despite the long history and evolution of CI methodology, ease of concepts and application, high amount of time and resources spent and furthermore proliferation of such deployments - the adoption and ultimately the success of such programs is highly variable. While many research papers and companies claim to have realized hundreds of millions in economic benefits from Lean deployments, just as many report to not even recover the cost of deployment. Researchers conclude that a complete systems approach to successfully deploy Lean methodology for long-term sustained gains is not widely understood or practiced. For this reason, in this research I present the design work of a new way to approach Lean/CI deployment methodology utilizing first-principles. The need for the new approach to deploying Lean/CI was engendered due to a mandate from the Senior Leadership Team (SLT) at the organization. The SLT desired a holistic approach that would align better to Company's Lean principles (first principles), show financial impact and bring about behavioral cultural change. This research presents the new approach - from First-Principles for the methodology, design criterion from SLT, to the design of the methodology, and then the application of the methodology to different businesses in the company. In essence, the research shows how any organization can build its own LMS utilizing first- principles to fit their own needs rather than copy pasting fragmented components offered by expensive consultants or snippets from literature – neither of w (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2021, Molecular Medicine

Successful manufacture of specialized human cells requires process understanding of directed differentiation. Here, we apply high-dimensional Design of Experiments (HD-DoE) methodology to identify critical process parameters that govern neural territory patterning from pluripotency—the first stage toward specification of central nervous system (CNS) cell fates. Using computerized experimental design, 7 developmental signaling pathways were simultaneous perturbed in human pluripotent stem cell culture. Regionally-specific genes spanning the anterior/posterior and dorsal/ventral axes of the developing embryo were measured after 3 days and mathematical models describing pathway control were developed using regression analysis. High-dimensional models revealed particular combinations of signaling inputs that induce expression profiles consistent with emerging CNS territories and defined critical process parameters for anterior and posterior neuroectoderm patterning. The results demonstrate the importance of combinatorial control during neural induction and challenge the use of generic neural induction strategies, like dual-SMAD inhibition, when seeking to specify particular lineages from pluripotency.

Master of Science, The Ohio State University, 2021, Public Health

Outpatient portal technology (OPP) can improve patient engagement. For pregnant women, this high level of engagement could have important implications for maternal and infant outcomes. There is a dearth in studies that characterize OPP use among pregnant women. Our academic medical center (AMC) implemented a system-wide OPP in 2011. The OPP includes functions that allow patients to access their personal health information (PHI), view and schedule appointments, and message their providers. Our study is among the few studies that characterizes OPP use in a historically understudied patient population. We built upon existing research using OPP server-side log files by executing a hierarchical clustering algorithm to group 7,663 pregnant women based on the proportion of use for each OPP function. We calculated proportions of use for each OPP function a woman engaged with and used these proportions as inputs for our cluster analysis. Women who visited a Maternal Fetal Medicine (MFM) provider for pregnancy were regarded as having high pregnancy-related risk, while those who only visited an Obstetrics and Gynecology (OB/GYN) provider were considered as having normal pregnancy-related risks. Post-hoc analyses were performed using one-way ANOVA to further assess OPP use on key encounter characteristics. Use of the following OPP functions was examined within the cluster analysis: Visits (manage appointments), MyRecord (access PHI), Messaging (send/receive messages), and Billing (view bills, insurance information). Our study sample was predominantly represented by non-Hispanic white women between the ages of 25 and 34. The most frequently used functions at the patient level were MyRecord, Visits, Messaging and Billing, with frequency of use similar between pregnancy risk groups. Median OPP function use plateaued by the third trimester for each pregnancy risk group, with significantly more use among women with a high-risk pregnancy compared to those with a normal pregn (open full item for complete abstract)

Master of Science in Computer Engineering, University of Dayton, 2021, Electrical and Computer Engineering

The growing demands for communication and complex network infrastructure relay on overcoming the network measurement and management challenges. Lately, artificial intelligence (AI) algorithms have considered to improve the network system, e.g., AI-based network traffic classification, traffic prediction, intrusion detection system, etc. Most of the development of networking AI models require abundant traffic data samples to have a proper measuring or managing. However, such databases are rare to be found publicly. To counter this issue, we develop a real-time network traffic generator to be used by network AI models. This network traffic generator has a data enabler that reads data from real applications and establishes packet payload database and a traffic pattern database. The packet payload database has the data packets of real application, where network traffic generator locates the payload in the capture file (PCAP). The other database is traffic pattern database that contains the traffic patterns of a real application. This database depends on the timestamp in each packet and the number of packets in the traffic sample to form a traffic database. The network traffic generator has a built-in network simulator that allows to mimic the real application network traffic flows using these databases to simulate the real-traffic application. The simulator provides a configurable network environment as an interface. To assess our work, we tested the network traffic generator on two network AI models based on simulated traffic, i.e., AI classification model, and AI traffic prediction. The simulation performance and the evaluation result showed improvement in networking AI models using the proposed network traffic generator, which reduce time consuming and data efficiency challenges.

Master of Science, The Ohio State University, 2021, Industrial and Systems Engineering

Capable computational technology is a necessary but not a sufficient condition for engineering a high-performing human-machine team (HMT). The interactions between human and machine agents can have substantial and surprising positive or negative effects on the overall performance of the system. This implies two requirements for robust HMT design: a set of design strategies to explicitly support joint cognitive functions and reliable techniques to evaluate how this support affects overall system performance. This study proposes simultaneous inference and data (SID) displays as a novel design technique to enable improved human-machine performance and joint activity graphs as a technique to evaluate this performance from a limited testing set. SID displays provide increased observability to computational algorithms by annotating a base data display with how the algorithm is interpreting the underlying data. Joint activity graphs compare performance of the joint HMT against the reference of the machine alone, extrapolating how each will perform outside the set of discrete testing cases. The results show SID displays enabled the HMT to significantly diverge from increasingly incorrect machine guidance, leading to substantial improvements in performance, especially when the machine guidance was wrong. Therefore, SID displays and joint activity graphs appear to be promising techniques for designing and evaluating joint cognitive systems that mitigate the negative consequences of incorrect machine guidance.

Doctor of Philosophy, University of Toledo, 2020, Manufacturing and Technology Management

The purpose of this research was to establish a case for the use of serious simulation games as a tool to enhance the learning of sales leadership skills. The study provides taxonomy around serious simulation games as a specific modality at the intersection of serious games and simulation games, which have a focus toward education. A literature review was used to build a research model to explain the factors that contribute to the effectiveness of an SSG deployed in a sales leadership program. In order to test the efficacy of this model, a sales leadership SSG was built for a sales leadership academic program. This SSG was built based on experience developing other programs, one specifically was a manufacturing game developed for Dana corporation. The research model was tested using a survey instrument, which was developed as the sales leadership SSG was being built. This instrument was used to collect self-reported responses from the students in the sales leadership course, which measured the factors around the efficacy of the SSG in this program. 166 students responded to the survey over five (5) semesters, and were analyzed using factor analysis and regression. The results demonstrated the efficacy of the theory, and supported 6 out of 7 of the hypotheses.

Master of Science, The Ohio State University, 2020, Industrial and Systems Engineering

Systems Engineering practice started in the 90s with aerospace industry. The motivation was to have a process for structural decomposition of a system during the design phase to the component level to reduce cost, risks, and errors as early as possible. Since then, the automotive industry has taken on the systems engineering practice. Systems engineering practice has traditionally used document-centric process in which after each phase of the design and implementation documents are created and then updated after changes. The major drawback of this process is its incompatibility with agile product development. Recently there has been a shift from a document-centric to model based systems engineering (MBSE). This work reviews the suitability of MBSE process for an agile product development by analyzing the effort required to create and maintain a system model in Cameo Enterprise Modeler using System Modeling Language as well as the cognitive system analysis of the project. EcoCAR's driver monitoring system is used for comparing the traditional document-centric system engineering and MBSE. This work shows that MBSE performs better in an agile environment where there are numerous iterations throughout the product life cycle.

Master of Science, The Ohio State University, 2020, Industrial and Systems Engineering

There is a large body of systems literature that studies and learns from adaptive team performance in high-complexity domains (nuclear, healthcare, aviation). However, there is little to no systems research on arguably the most popular team setting: organized sports. Using converging methods, this study looked at (1) patterns of adaptation that are revealed when using a resilience engineering lens to look at intra- and inter- game coaching decisions, and (2) the strategies that coaches use to affect individual and system performance on a collegiate basketball team. The specific concepts borrowed from resilience engineering used to view this domain were common ground, mutual directability, interpredictability, polycentric control and being poised to adapt, amongst others. A resilience engineering lens was used due to the fact that it is known to be critically important to other complex adaptive systems. Decision-making and adaptations in sports are commonly thought to be targeted towards each individual. Through structured interviews, this study found that there are hidden triggers and decision-making processes that are system-focused rather than individually-focused when coaches assess the need for an adaptation and execute it. In addition, the existence of different time scales to implement and execute adaptations was found to be a critical point that coaches exploit in order to increase the readiness to adapt during high tempo periods. Basketball has high varying tempos on multiple time scales, from longest to shortest: practices and film sessions between games, halftime breaks, timeout breaks, play breaks and in-play breaks. This study identifies various hidden system level strategies that coaches use in order to achieve successful team performance across the different time scales: increasing the levels of common ground, directability, predictability, readiness to adapt and polycentric control. For example, this research found that the development of coded ter (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2020, Counselor Education and Supervision

Youth are at risk of out of home placement for varied reasons, which places excess burden and negative consequences on youth, families, communities, and stakeholders. This creates a need to identify effective, adherent treatment to avoid placements. This quantitative research study utilized a general systems theory and implementation science framework to assess if adherence to Intensive Home-Based Treatment (IHBT) impacted case outcomes at discharge. A Columbus, Ohio IHBT program's outcomes were analyzed, with a sample size of 116 participants. A simple linear regression approach of ordinary least squares regression analysis was utilized with SPSS. Variables analyzed included adherence measured by the IHBT Caregiver Feedback Survey (Shepler, et al., 2016) and youth outcomes measured by change in hospitalization, and change in problem severity and functioning on the Ohio Scales- Parent Form (Ogles, 2000) from intake to discharge. Initial results were not statistically significant as variables were not correlated. To further inform the original research question and determine if outcomes were positive despite adherence not being significant, a post-hoc analysis using a t-test for dependent samples was conducted. It determined there was a statistically significant difference between the mean scores from pre-IHBT to post-IHBT, as youth had a decrease in hospitalization, made clinically significant changes in problem severity, and showed reliable change in functioning. This suggests that IHBT is an effective treatment for youth with serious emotional disturbance and risk of out of home placement.

Doctor of Philosophy, Miami University, 2019, Educational Leadership

Research reveals that there is often a major disconnect between leaders and workers in organizational settings, especially when it comes to decision-making. Consequently, organizational decisions are often misunderstood by the employees who must implement top-down directives, which can lead to growing distrust, frustration, and needless resistance toward change initiatives. This kind of disconnect, resulting confusion, and resistance is also found in schools between principals and teachers. Having worked as a teacher and then as an administrator in three separate school districts, I have become overwhelmed by the bureaucratic nature of school committees. In my experience, school committees tend to be exclusive, administrator-driven, and lack authentic, rich discussion. This study seeks to narrow the focus of research on school committees by exploring how teachers experience the decision-making process for change initiatives in a school committee setting when inclusive deliberation (ID) is used as a framework for school committee design. Also, the study explores the impact of school committee design and operation on teacher resistance and feelings of morale. The methodology of this study is a single instrument, action research case study, expressed in a narrative. The case exists at the high school where I work as an assistant principal. During the second semester of the 2018-2019 school year, a committee known as the Building Leadership Team (BLT) altered its design and operation, using the framework of inclusive deliberation (ID). Teachers' experience with the BLT, along with other phenomena that took place during the case study with additional members of the staff, were collected as data. Data was collected through observational field notes, journaling of daily interactions, participant reflection prompts, staff surveys, a focus group reflection, and individual interviews. Inductive analysis was used to triangulate the data to understand the phenomena being resear (open full item for complete abstract)