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THE POTENTIAL OF FOOD-TO-FOOD FORTIFICATION WITH TURKEY BERRY AND COWPEA LEAF POWDERS TO ENHANCE DIETARY IRON AND FOLATE INTAKE AMONG WOMEN OF REPRODUCTIVE AGE : FROM PROCESSING TO BIOAVAILABILITY
No full textThesis (Ph.D.)--Michigan State University. Food Science - Doctor of Philosophy, 2024Iron and folate deficiencies are critical public health challenges in low- and middle-income countries, particularly among women of reproductive age and children. Food-to-food fortification with indigenous foods has been suggested as a complementary approach to traditional food fortification and supplementation strategies in resource-poor settings. However, research gaps persist regarding the effectiveness of this strategy for women of reproductive age, particularly concerning processing challenges and the impact of different methods on nutrient retention, as well as the acceptance of fortified foods. Additionally, the bioavailability of iron and folate from food fortificants and their contribution to dietary intake among women in Ghana have not been adequately explored. This study tested the hypothesis that food-to-food fortification with two locally available vegetables, turkey berries, and cowpea leaves would significantly enhance dietary iron and folate intake among women of reproductive age and possibly children in Ghana. The research focused on: (1) overcoming common processing challenges such as color degradation and drying kinetics in turkey berries, and (2) evaluating the effects of various processing methods on the physicochemical properties, including iron content in both vegetables and folate, a water soluble-heat-labile vitamin in cowpea leaves, and (3) assessing iron bioavailability in the powders and fortified culturally acceptable tomato-based soup and mango-banana-based smoothie, as well as acceptability of the fortified foods among African women of reproductive age. The findings indicated that excessive browning and prolonged drying times in turkey berries were mitigated with appropriate pretreatments, specifically blanching and osmotic treatments. We developed optimal kinetic models for color degradation and drying kinetics in turkey berries, providing a useful tool for researchers and food processors. Cowpea leaves, although underutilized, were found to contain significantly higher levels of iron and folate than turkey berries, which are widely recognized in Ghana for their purported anti-anemic properties. However, both powders showed low iron bioavailability. Steaming emerged as the most effective method for retaining iron, folate, and other bioactive compounds in cowpea leaves, compared to boiling, which is typically used for domestic cooking. Cowpea leaf-fortified tomato-based soup contributed up to 26% of the recommended daily allowance (RDA) of iron and 12% of the RDA of folate per serving for women. The soup could potentially contribute up to 100% of the RDA of iron and 48% of the RDA of folate per typical Ghanaian adult soup portion of up to four cups. The mango-banana-based smoothie provided 16% of the RDA of iron and 9% of the RDA of folate per serving. Iron bioavailability was high in the unfortified soup, but low in the unfortified smoothie. Adding cowpea leaf powder reduced iron bioavailability in the soup but had no significant impact on the smoothie. Regarding perceptions and acceptability of the fortified foods, there was a general preference for fresh vegetables, among a group of African women who were however willing to incorporate cowpea leaf powders in their foods, especially for children and use the fortified smoothie and the soup for their potential health benefits. Raw cowpea leaf powder can be used to enrich soups and stews, while steamed powder is ideal for ready-to-eat foods like smoothies, especially in Northern Ghana, where micronutrient deficiencies are common, and fresh leaves are a staple. Exploring the development of innovative food products with enhanced bioavailability using cowpea leaves and turkey powders, is a promising approach. These products should be designed to integrate seamlessly into culturally accepted foods while providing optimal nutritional benefits. Coupling this with targeted nutrition education is critical for successful adoption of food-to-food fortification.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Change the Story, Change the Curriculum : The Curriculum-as-Story Metaphor as a Flexible Lens for Interpreting Curricular (In)Coherence from Students' Perspectives and Beyond
Get PDFThesis (Ph.D.)--Michigan State University. Mathematics Education - Doctor of Philosophy, 2024A common educational assumption is that coherence is a pre-requisite for a \u201cgood\u201d curriculum. Indeed, in mathematics education this perspective has persisted both nationally and internationally as a foundational principle for curriculum design, reform, and evaluation. While curricular coherence is often unquestioningly accepted as desirable for student learning, some researchers have urged caution, arguing that \u201ccurricular coherence\u201d is loosely defined with no widespread agreement over its meaning. Yet, disciplinary, logico-rational forms of coherence (i.e., retrospective expert perspectives) tend to dominate curricular discourses in mathematics education, often in ways that position these disciplinary forms of coherence as objective evaluations of curricula. Other perspectives on what it means for curricula to be \u201ccoherent\u201d\u2014particularly those of students\u2014are rarely centered, which has epistemological as well as ethical consequences for who/what is positioned as coherent (i.e., \u201cideal\u201d) and who/what is positioned as incoherent (i.e., abnormal, aberrant, incomplete). This binary imposes a distribution of \u201csensible\u201d mathematics learning, thereby perpetuating a harmful culture of exclusion in mathematics education. In this dissertation, I critically investigate curricular coherence in mathematics education by interrogating the notion of coherence itself and problematizing the dominance of a singular perspective on coherence. To do so, I conceptualize curriculum as a storied artform and view coherence as an individual\u2019s holistic aesthetic judgement of curricular stories. These judgements are highly subjective and may vary from person to person as well as discipline to discipline, destabilizing the myth that curricular coherence is an objective evaluation with a singular definition. Rather, I contend that curricular coherence must be defined kaleidoscopically via a plurality of disciplinary and stakeholder perspectives. To this end, I investigate three interrelated questions: (1) Ontologically, what is coherence in its many forms? In other words, what does \u201ccoherence\u201d refer to in both mathematics and science education, as well as in other disciplines? Additionally, according to these ontologies, who is positioned with the authority to make judgements or evaluations of (in)coherence? (2) What are the aesthetic, ethical, and onto-epistemological foundations behind the common (and often implicit) assumption that coherence (in its many forms) is desirable? What are the consequences of these philosophical assumptions for curriculum? For learning? For how learners as positioned? In other words, I question curricular coherence for what purpose? (3) Finally, what are the flexible possibilities (and tensions) for conceptualizing curriculum using an aesthetic curriculum-as-story metaphor to investigate various forms of curricular (in)coherence from multiple stakeholder perspectives? I inquire about these overarching questions through three interrelated studies\u2014one theoretical and the other two empirical\u2014situated within an arts-based research paradigm. These investigations serve as a type of disciplinary-cultural analysis and artistic critique from both my own and students\u2019 perspectives with the overriding goal of interrogating and shifting the normative value of (curricular) coherence in mathematics education. More broadly, this dissertation spotlights the aesthetic dimension of learning mathematics as well as the danger of divisive and dehumanizing politics of aesthetics inherent to uncritical conceptualizations of so-called \u201cdesirable\u201d modes of teaching and learning, such as the privileged logico-rational definition of curricular coherence that is the current status quo.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Dynamic Response and Kinetic Phenomena in High Energy Density Multi-species Plasmas
No full textThesis (Ph.D.)--Michigan State University. Physics - Doctor of Philosophy, 2024High energy density (HED) science, concerned with matter at pressures in excess of 1 MBar, investigates the processes occurring inside nuclear fusion and giant planets, enhancing our understanding of the universe's most energetic events. This work contains three primary results. First, we incorporate conservation of momentum into the collisional multi-species dynamic response models. Second, we extend the single species hybrid kinetic-fluid model of Degond et al. to multi-species [P. Degond, S. Jin, and L. Mieussens, JCP 209.2 (2005): 665-694]. Third, we present data-driven observations of system equilibration, which can assess the quality of machine-learned model closures in extended moment hydrodynamics. Each result uses expansions about equilibrium, but contributes to HED science in different ways.Measuring the material properties of HED matter is challenging since they exist for a short time in a confined space at conditions that damage nearby equipment. Thus, experimental diagnostics rely on scattered and emitted electromagnetic spectra to investigate material properties. Connecting the spectra to material properties requires theoretical models of dynamic response. Typical dynamic response models include the Mermin model, predicting Drude-like conductivity [N. D. Mermin, PRB 1.5 (1970): 2362], and the Drude-Smith model, predicting non-Drude-like conductivity [N. V. Smith, PRB 64.15 (2001): 155106]. However, the often used Mermin model does not satisfy the relevant sum rules, and the Drude-Smith model lacks interpretability. In this dissertation, develop a new interpretable dynamic dielectric function for multi-species plasmas which includes mean field interactions as well as number and momentum conserving multi-species collisions. This interpretable model satisfies relevant sum rules. We demonstrate the impact of each conservation law on the predicted dynamic structure factor of a pure deuterium-tritium (DT) HED plasma as well as a carbon contaminated DT HED plasma. Additionally, we present a new dynamic non-Drude conductivity model that has a clear interpretation. Comparing our conductivity model to the Drude-Smith conductivity model, we conclude that Smith\u2019s intensely debated phenomenological parameter violates local number conservation.Simulations are conducted to complement and inform HED experiments. Historically, HED scientists have used radiation\u2013hydrodynamic codes. However, Eulerian codes assume the mean free path in the plasma is infinitesimally small, placing the system in local equilibrium. This assumption neglects dissipation and forces species in the same location to share a bulk velocity and temperature. Current codes correct for dissipation, which improves predictions, but they cannot correct for velocity and temperature separation. A fully kinetic code could account for these phenomena, but such a code is computationally infeasible for realistic 3D simulations. In this dissertation, we present a hybrid model which can smoothly transition between Haack et al.'s multi-species kinetic PDE [J. R. Haack, C. Hauck, and M. S. Murillo, J. Stat. Phys. 168, 4] and multi-species hydrodynamic PDEs. We validate the hybrid model on the Sod shock problem and then investigate multi-species mixing in HED experiments. Within our simulation, we identify electro-diffusion at the interfaces as well as persistent velocity and temperature separation between species, phenomena that are missed by purely hydrodynamic codes.As an alternative to hybrid models, extended moment hydrodynamic models can be employed [N. M. Hoffman, et al. Physics of Plasmas 22.5 (2015)]. However, to close the hierarchy of moments, these models often assume local equilibrium. Machine learning is an emerging approach to the moment closure problem, which can avoid such assumptions. We construct a complex-valued, multi-step neural network to close Grad's extended moment equations [H. Grad, Comm. pure and applied mathematics 2.4 (1949): 331-407]. Additionally, the quality of a closure is typically assessed on its long time stability and ability to describe diffusion/dissipation. We conduct data driven observations of the dissipation process. In particular, we use dimension reduction techniques and dynamic mode decomposition to provides new metrics to assess a neural network's ability to inform on dissipation.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Seismic studies of western Pacific subduction zones with high-performance computing and deep learning
No full textThesis (Ph.D.)--Michigan State University. Computational Mathematics, Science and Engineering - Doctor of Philosophy, 2024In this dissertation, I explore seismic phenomena across the Western Pacific subduction zones, employing computational techniques to analyze and interpret complex geophysical data. The study is structured into focused chapters, each contributing to a comprehensive understanding of the seismic velocity structures and the mechanisms driving deep earthquakes in this region.Chapter 1 provides an overview of subduction zones, crucial regions where one tectonic plate is forced below another, leading to significant geological phenomena such as earthquakes and volcanic activity. Focusing on the Western Pacific, the chapter examines the complex interactions at the subduction zones formed by the convergence of the Pacific and Philippine Sea Plates, especially in the northern regions, and the unique geological setting of the Tonga subduction zone and the Lau back-arc basin in the south. These zones are vital for understanding the mechanics of plate tectonics and the resulting seismic activity. Through a detailed examination of the Earth model and seismicity, the chapter sets the groundwork for the dissertation's main scientific inquiries, aiming to unravel the processes governing seismic phenomena in these tectonically active regions using seismic imaging and machine learning techniques.Chapter 2 introduces EARA2023, a detailed seismic velocity model of the crust and upper mantle beneath East Asia and the northwestern Pacific. This model, constructed through adjoint full-waveform inversion tomography, is based on waveform data from 142 earthquakes and broadband records from around 2000 stations. EARA2023 offers enhanced images of the subducted oceanic plate, detailing complex slab deformations and providing new perspectives on the origins of notable intraplate volcanoes in East Asia, such as Changbaishan, Datong-Fengzhen, Tengchong, and Hainan.Chapter 3 shifts the focus to the application of machine learning for detecting deep earthquakes, specifically within the Tonga subduction zone. This part of the research outlines the development of a deep-learning-based workflow centered around PhaseNet-TF, a new phase picker designed for the time-frequency domain analysis. This method proves particularly effective for analyzing data from ocean-bottom seismographs (OBSs), improving the detection and picking of P- and S-wave arrivals. The chapter discusses the integration of this technology with an improved Gaussian Mixture Model Associator and the application of a semi-supervised learning approach to refine earthquake catalogs, thereby enhancing our understanding of the seismic activity in the Tonga region.Chapter 4 further advances the discussion by examining the use of converted seismic phases, with an emphasis on PS waves from deep earthquakes in the Tonga subduction zone. The chapter explores the application of PhaseNet-TF to identify PS-converted wave arrivals, alongside direct P and S phases, and details the use of beam-forming and a Markov chain Monte Carlo method for associating detected phases. This approach significantly increases the detection of PS arrivals, contributing to a higher resolution imaging of the subducted slab and offering insights into the structural seismology of the Tonga subduction zone.Collectively, these chapters present a narrative that not only highlights the utility of computational methods in seismic research but also provides a deeper understanding of the mechanisms underlying seismic activity in the Western Pacific. This dissertation contributes to the field of seismology by demonstrating the potential of combining seismic modeling, machine learning, and the analysis of converted seismic phases to investigate subduction zone dynamics and deep earthquake mechanisms.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
EFFECTIVENESS OF BEHAVIOR SPECIFIC PRAISE DURING ACADEMIC ACTIVITIES
No full textThesis (M.A.)--Michigan State University. Applied Behavior Analysis - Master of Arts, 2024In this study, researchers examined the effects of behavior specific praise in early childhood special education classrooms during academic activities. Child participants demonstrated challenging behaviors which inhibited their ability to attend during academic instruction. An AB case design was used to evaluate the effects of behavior specific praise on child behavior. Results show promise for use of behavior specific praise to increase on-task behavior and decrease challenging behaviors for one participant. Implications for future research include the need to further assess the extent to which behavior specific praise increases on-task behavior and decreases challenging behavior as well as additional variables such as schedule of delivery of behavior specific praise and matching child interest to activities.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
A Ghost of Herself : Female Spectrality and the Undead Madwoman
No full textThesis (M.A.)--Michigan State University. Literature in English - Master of Arts, 2024The specter has long been a figure of study within Victorian literary criticism. Haunting dark stairwells and appearing in the reflection of windows, the Victorian specter is known for bringing madness to those who perceive it. While many have discussed the Victorian specter and its connection to madness, there remains a gap in the scholarship surrounding female spectrality and the role the specter plays in representing female mental illness. While the early nineteenth century was known for classic ghost stories, there was also an emerging body of literature \u201c[that] aimed to provide \u2018rational\u2019 and scientific explanations for widely believed supernatural events\u201d (Mangham 283). This shift largely has to do with an increased interest in psychological study and what the Victorians called the sciences of the mind. As Suzy Anger notes, the Victorians \u201cread and wrote widely on subjects connected to the mental sciences\u201d with conversations about the mind appearing in popular periodicals, magazines, and newspapers (Anger 276). These conversations in turn had an influence on popular fiction of the time. Through an examination of spectrality and madness in The Woman in White by Willkie Collins and Wuthering Heights by Emily Bronte, I will demonstrate how madness is used as a social label to subjugate women to an undead existence and how Collins and Bront\ueb offer their texts as depictions of as well as interventions against this subjugation. This reading will be supported by an analysis of the material in the periodical press Collins and Bronte would have been reading at the time, drawn from Blackwood\u2019s Edinburgh Magazine and Household Words, to demonstrate how this critical work was beginning in these periodicals, largely, through their braiding together of conversations related to madness, spectrality, and the mental sciences.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
MACHINE LEARNING FOR TRANSITION METAL COMPLEXES
No full textThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2024Transition metal complexes, dubbed \u2018Lego molecules\u2019, are composed of small molecules, ions, or atoms arranged around a central metal. The diversified research field of organometallic compounds includes but is not limited to the study of metal- ligand interactions, structure-property relationships, and practical applications. This dissertation leverages machine learning techniques to expedite the research in this domain. The first part focuses on neural network potentials (NNPs). A Zn_NNPs model was built to depict the potential energy surface of zinc complexes. In this work, a simple but useful embedding of partial charges was proposed, which could model the long-range interactions accurately. Furthermore, an Fe_NNPs model was designed to identify the lowest energy spin state of Fe (II) complexes. The model integrates electronic characteristics such as total charge and spin state to account for long-range interactions effectively. For each model, a high-quality data set including tens of thousands of distinctive conformations was well curated using metadynamics. The third model is a scaffold-based diffusion model, called LigandDiff which can generate valid, novel, and unique ligands for organometallic compounds. Users only need to specify the desired size of the ligand, LigandDiff then generates a diverse and potentially infinite number of ligands of that size from scratch. Collectively, these models surpass traditional computational methods on both accuracy and efficiency, demonstrating substantial potential to acceleratetransition metal complexes research.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ASSOCIATIONS BETWEEN AREA-LEVEL DEPRIVATION AND PRETERM BIRTH IN THE BIBB (BIOSOCIAL IMPACT ON BLACK BIRTHS) STUDY
No full textThesis (Ph.D.)--Michigan State University. Epidemiology - Doctor of Philosophy, 2024Evidence suggests that neighborhood deprivation may be associated with an increased risk of preterm birth (PTB, <37 weeks completed gestation). Black women, specifically, are more likely to have PTB and reside in deprived neighborhoods than their white counterparts. Few prior studies have examined this relationship in a cohort comprised solely of Black women and at multiple spatial levels. Our objective was to examine the association between area-level deprivation and the odds of PTB at the county, minor civil division (MCD), and census tract level in a Black cohort, and to determine if this association is modified by individual-level maternal characteristics. Women consented to participate in the BIBB study during a prenatal care visit and were surveyed to obtain addresses and individual-level data on age, income, and education among other covariates (n=1,239). Prenatal and hospital birth records of women who participated were abstracted to obtain multiple measures from which to categorize PTB. After exclusion for spontaneous abortion, therapeutic abortion, stillborn, or fetal death (n=17); women with missing gestational age data (n=47); missing residential address data (n-63); or lived in a Census tract that could not be linked to Census data (n=1); 1,112 women remained in the final sample size. Addresses from participants were geocoded and linked to data from the American Community Survey 5-year estimates. Six individual area-level characteristics were selected a priori for analyses: percent of population identifying as Black, unemployment rate, median household income, percent of population that is college educated, vacant housing rate, and percent on public assistance. An area-level deprivation index (ADI) was developed from a principal components analysis of the variables at the 3 aforementioned spatial levels. To examine the association between the ADI and the odds of PTB, odds ratios and 95% confidence intervals were estimated with sequentially-built generalized estimating equations (GEE). Models with the best fit were selected using the quasilikelihood information criterion (QIC). Effect modification by individual-level maternal characteristics, such as income and education, was also assessed using GEE. After controlling for maternal age, annual household income, and education level, no association was found between the ADI and the odds of PTB at the county and Census tract levels. At the MCD level, however, living in the most deprived neighborhood quartile, compared to living in the upper three quartiles, was found to be slightly protective of PTB (OR = 0.90, 95% CI: 0.84, 0.96). There was statistically significant effect modification of the association with PTB by maternal annual household income at all three spatial levels. Among women who resided in the highest quartile of area-level deprivation, women who were low income (< 30,000/year) counterparts. We simultaneously examined effect modification by maternal annual household income and education level in a two two-way interaction model at the Census tract level. Among those with an annual household income of over 30,000 and who were college educated, living in a high deprivation Census tract was associated with a 59% decrease in odds of PTB compared to those residing in a low deprivation Census tract. Area-level deprivation is a multidimensional construct that may influence a woman\u2019s odds of PTB in several ways, and the impact it has on odds of PTB may vary across different spatial levels. Future research should further examine the association between area-level deprivation at multiple spatial levels and PTB risk, and further explore how this relationship may be moderated by various individual-level characteristics.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Advanced Statistical and Computational Techniques for Genomic Data Analysis
No full textThesis (Ph.D.)--Michigan State University. Statistics - Doctor of Philosophy, 2024The human body is an incredibly complex system that researchers have studied for decades to uncover its secrets. Genetic, transcriptomic, and epigenetic data each offer unique insights into its functioning. Recent technological advancements have enabled the generation of vast amounts of high-quality biological data, creating unprecedented opportunities to explore molecular mechanisms underlying health and disease. Analyzing these diverse datasets is crucial for developing targeted therapies, personalized medicine, and advancing our understanding of biology. Building advanced statistical and computational models to handle these complex datasets is now more important than ever for translating biological information into actionable insights and driving breakthroughs in medical research and treatment strategies. In this dissertation, I first developed BayesKAT, a kernel-based testing methodology for assessing the association between user-defined groups of SNPs or genes and a phenotype of interest (Chapter 2). Unlike existing kernel-based tests that use predefined single or average kernels and often yield ambiguous results, this algorithm adaptively selects the optimal composite kernel using a Gaussian process model within a Bayesian framework, providing more interpretable outcomes. Next, I explored the emerging field of spatial transcriptomics, where similar Gaussian process models and kernel-based testing have significant potential. To complement the recent surge in spatial transcriptomics research, Chapter 3 presents a comprehensive literature review of significant methodologies, particularly for spatial gene detection, which is a crucial step in spatial transcriptomics data analysis. This review provides an overview of the current state of research in the field. In Chapter 4, I extended the kernel-based testing procedure to address challenges in spatial transcriptomic data. The newly developed algorithm, cSVG, not only detects spatially variable genes, but also improves spatial domain detection accuracy and addresses additional problems in this field. Finally, to tackle the scarcity of crucial TF binding information for many transcription factors (TFs) across various cell types, I developed a computational model, 3D-TF-IMPUTE (Chapter 5). This model predicts TF binding sites by utilizing readily available epigenetic datasets and leveraging the three-dimensional structure of the genome in an unsupervised manner, efficiently predicting TF binding sites essential for understanding the functional genome. By tackling key challenges in the analysis of genetic, transcriptomic, and epigenetic data, this dissertation makes significant contributions to the field. It provides powerful tools for researchers to better understand the molecular underpinnings of health and disease, paving the way for future breakthroughs in biomedical research.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
OPENING THE NEGOTIATION SYSTEM : AN INITIAL EXAMINATION OF A MULTISTAGE AND MULTILEVEL FRAMEWORK
No full textThesis (Ph.D.)--Michigan State University. Business Administration - Organization Behavior - Human Resource Management - Doctor of Philosophy, 2024Negotiation scholars have attributed practitioner-researcher and researcher-researcher divides to a closed system paradigm embedded in the literature. This paradigm remains embedded despite calls to adopt an open system paradigm. However, presently there are no open system frameworks precise or prescriptive enough to facilitate the needed research. This dissertation addresses this research need in three sections. First, the theoretical foundations section expands upon existing theory on conflict management in teams and negotiations to define key dimensions of an open system. The first dimension focuses on Time and organizes the flow of the negotiation process. The second dimension focuses on Levels and articulates how the negotiation process unfolds across strata of social structures. The resulting theoretical framework comprises a novel contribution to the negotiation literature and greatly expands the traditional scope of negotiation research. Second, the systematic review section utilizes this theoretical framework to organize and critically evaluate recent publications in top negotiation outlets. Beyond synthesizing existing findings, this systematic review identifies numerous areas of the open system framework that are considerably understudied as well as areas of the open system framework where conventional wisdom is unlikely to hold true. Third, the empirical section examines one such area. Specifically, conventional wisdom holds that integrative strategies will outperform distributive strategies is optimizing joint outcomes. However, when challenges during agreement implementation necessitate a return to the bargaining table, integrative strategies can underperform distributive strategies. This study marks the first empirical examination of a multi-episodic negotiation involving the same partners working on the same task. The implications of the specific findings and the general framework of this dissertation to both practitioners and researchers are discussed.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references