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The yeast Saccharomyces cerevisiae genome is descendant from a whole genome duplication event approximately 150 million years ago. Following this duplication many genes were lost however, a certain class of genes, termed ohnologs, persist in duplicate. In this thesis we investigate network centrality as it relates to ohnolog re- tention with the goal of determining why only certain genes were retained. With this in mind, we compare physical and genetic interaction networks and genetic and pro- tein sequence data in order to reveal how network characteristics and post-duplication retention are related. We show that there are two subclasses of ohnologs, those that interact with their duplication sister and those that do not and that these two classes have distinct characteristics that provide insight into the evolutionary mechanisms that affected their retention following whole genome duplication. Namely, a very low ratio of non-synonymous mutations per non-synonymous site for ohnologs that retain an interaction with their duplicate. The opposite observation is seen for ohnologs that have lost their interaction with their duplicate. We interpret this in the fol- lowing way: ohnologs that have retained their interaction with their duplicate are functionally constrained to buffer for the other ohnolog. For this reason they are retained; ohnologs that have lost their interaction with their duplicate are retained because they are functionally divergent to the point of being individually essential. Additionally we investigate small scale duplications and show that, generally, the mechanism of duplication (smale scale or whole genomes) does not affect the distri- bution of network characteristics. Nor do these network characteristics correlate to the selective pressure observed by retained paralogous genes, including both ohnologs and small scale duplicates. In contrast, we show that the network characteristics of individual genes, particularly the magnitude of their physical and genetic network centralities, do influence their retention following whole genome duplication. / Graduate / mjrimrie@gmail.com

<p>In situations of armed violence and insecurity, how do civilians influence the political environment around them? In this dissertation, I present three different studies that broadly engage this question. In concert, the papers presented herein offer new insights on civilians' relationship to armed conflict through a focus on victimization, participation, attitudes on resistance, and the effects of civilian resistance on aggregate levels of violence. </p><p>The first study explores the effects of victimization on political participation. I argue that previous answers to this question have overlooked a key variable for predicting civilian behavior: individual level social context. As a step forward in connecting social support networks to behavioral outcomes, I present the kinship network as a novel measure that captures an individual's valuable and private social interactions. I find that survivors of criminal violence with strong ties to kinship networks are most likely to attend political meetings. By highlighting variation in behavior across victims, I challenge previous work which only examines differences in participation between victims and non-victims. </p><p>Motivated by the assumption that attitudes are a precursor to action, my second study examines civilian attitudes on the efficacy of resistance in regions of protracted violence. Using an original survey fielded in Mexico, I explore the conditions under which civilians are likely to view nonviolent or violent methods as useful tools for change. I first test whether several demographic factors--age, gender, income, knowledge about civil resistance, and media consumption--influence attitudes toward resistance. Moving beyond these variables, I then test whether perceptions about government responsibility affect these attitudes. Specifically, I argue that civilian attitudes towards resistance methods are informed by which political actor civilians view as responsible for their security problems. I find that the predicted probability of viewing nonviolent action as more effective than violent action increases by 20.8% for those who attribute security responsibility to local authorities, compared to other actors. Using an embedded survey experiment, I then address the empirically relevant question of whether these attitudes about resistance correlate with action. I find that compared to those who do not view resistance as useful, respondents who view nonviolence as effective are "supportive types'' who are more willing than others to support local resistance groups, regardless of the methods these groups employ. Together, these analyses provide important information for civilian organizers seeking to mobilize latent support for resistance. Moreover, they enrich our understanding of the ways in which communities can reduce violence in order to reclaim political control during armed conflicts.</p><p>Last, I present an aggregated analysis on the evolution of armed conflict in Mexico. The criminal war in Mexico is extremely complex: Drug Trafficking Organizations, citizens, government agents, amongst others, are all relevant actors within the dynamic evolution of the conflict. Existing research, however, typically ignores the interdependencies inherent to these networks. Using a new collection of machine-coded event data, I generate conflict networks for each year from 2004 to 2010. In doing so, I make three major contributions. First, I offer insights into the potential promise and pitfalls of using machine-coded data for country-level analysis. Next, after cleaning and improving upon the original data, I generate yearly networks, which capture a wide range of violent-related actors. Importantly, I demonstrate how these networks illustrate the interdependent nature of the Mexican conflict and present new insights, such as how government coordination changes in response to cartel violence over time. Finally, I use a latent space approach to identify previously unobservable violence between government actors, criminal groups, and civilians. This research design serves as a platform for future research to investigate the effects of major civilian-led events--such as mass protests--on the evolution of armed conflict.</p> / Dissertation

Generating innovative solutions for large-scale multifaceted problems increasingly requires the carefully orchestrated coordination and collaboration of complex collectives composed of multiple teams. However, there are many difficulties inherent in collaborative work, which are often exacerbated when individuals hail from multiple fields, perspectives, cultural backgrounds, and geographical locations. Although collective creativity can be maximized when teams leverage functionally diverse information, often residing outside the boundary of the team, this is only true to the extent that teams can effectively reconcile often-competing perspectives. Resolving these countervailing pressures requires leadership networks - patterns of emergent influence - that enable organizational teams to explore and exploit diverse informational sets. In this thesis, I turn to leadership networks in order to understand how the social structure of influence within cross-functional multiteam systems (i.e., MTSs) holds the potential to catalyze innovative new ideas. I evaluate hypotheses about the structure of leadership networks and resulting creative output in a sample of geographically distributed cross-functional MTSs formed using students completing linked semester-long projects across two universities in the US and France. Findings reveal the structure of leadership networks, both during early exploration and later exploitation phases, has important downstream consequences for innovation. First, my results suggest that throughout exploration and exploitation, innovation arises in those MTSs who exhibit leadership networks high in bridging ties and whose leaders have strong mutual influence on one another. Second, I find innovation arises in those MTSs whose leadership networks are highly concentrated around a relative few members during the exploitation phase.

Individuals, communities, non-government organizations and governments are in constant pursuit of intelligent responses to the complex socio-environmental challenges they encounter. The capacity to respond effectively to these contemporary challenges is deeply dependent on the presence of effective governance processes. Governance scholarship has typically been limited to individual elements such as frameworks (hierarchical or market or network), tools (e.g., regulation) or actors (e.g., government). The goal of this thesis is to characterize and explain transformations in water governance in order to offer insight into how more effective governance processes can be created. Transformations in governance speak to the dynamic nature of governing, and highlight the consistent push and pull between, and amongst, the various components at play. Components include actors, formal and informal structures, and the social, economic and environmental contexts in which governance is embedded. Critically each of these components also exists and has influence at multiple levels, adding to the complex and dynamic nature of governance. This research argues that the core elements (frameworks, tools, actors) should be examined individually, as well as collectively, and within context of the various components in order to obtain a holistic perspective on governance process. This holistic perspective is necessary if we are to garner a true understanding of how governance is ultimately designed, contested and transformed. The research focuses on a large-scale water governance case in southern Ontario that is governed by its own provincial legislation ??? the first of its kind in Canada. The research examines governance frameworks as situated within the broader architecture, tools, and actor dynamics in the Lake Simcoe watershed and how they evolved over a 30-year period. Interviews, archival research, surveys and social network analyses were utilized in a mixed methods approach. The first governance element examined in this thesis is the architecture of the entire system over the 30 year time period. Rather than conduct a narrow analysis of an individual governance framework in a select period of time, the research takes a high level perspective to identify the transitions between governance frameworks, and the social, economic, and environmental tensions and drivers that initiated change. Particular value is offered by the use of social network analysis to visually identify the structure and statistically evaluate the governance framework at multiple phases in the research period. The second element of governance, tools, is then assessed. Specifically, the utility of a watershed boundary for water governance is examined. The thesis argues that the watershed boundary has value, but should be applied in limited and focus ways, and greater attention should be given to governance processes that transcend the watershed boundary. The final element examined is actors. Early in the thesis, focus is given to the role of government, but in the final section particular attention is given to the role of non-government actors. The research describes how the role and activities of non-government actors has advanced beyond late 20th century approaches, where recent trends display more innovative and entrepreneurial characteristics. The research offers nine important insights for theory and practice in water governance. (1) Governance processes have the potential to be flexible, adaptive and responsive. (2) A reduced presence of government does not always hold back processes of governance. (3) Existing tools can be re-imagined for new processes. (4) Non-government actors have agency (5) Give attention to individual knowledge and capacity through a distributed governance approach (6) Give attention to time and the building of scientific knowledge (7) Give attention to need for effectively facilitated processes (8) Give attention to emerging opportunity (9) Permits space for creative destruction. Collectively, the findings from this research further develop scholarship on the individual elements of governance, as well as speak to the transformations in water governance as a whole.

Studies of adaptive governance in social-ecological systems have identified common features that assist social actors in responding to environmental pressures. Among these features, multiple sources of ecological knowledge, trust, and networks between actors have been highlighted as properties that contribute to successful governance arrangements. However, studies in adaptive governance have also been critiqued using a political ecology approach. This is due to their under-theorization of political elements that can constrain or promote the formation of the features of adaptive governance. In particular, power dynamics between actors and the subsequent privileging of one source of knowledge over another might have an effect on governance arrangements. In China, environmental degradation is a serious issue. The Qinhuai River, located in the city of Nanjing, has experienced significant ecological decline over the last 30 years as urbanization pressures on the system increased. Over the same period, China has undergone changes in state-society relations, including allowing the formation of NGOs. Since the turn of the millennium, several NGOs have begun working on issues related to the Qinhuai River, including raising awareness and producing information on the environment. This study examines the features of adaptive governance in a critical light by situating them in the local political context of China. The relationship between NGOs, fishers who use the Qinhuai River and government are examined using Social Network Analysis and semi-structured interviews in order to understand the production of information, networking and trust between these actors. It is shown that the existing arrangements to include NGOs and fishers in the river’s governance activities are guided by a corporatist system of state-sanctioned representation. This is not conducive to adaptive governance arrangements, despite the increasing existence of ENGO networks and new sources of knowledge over the last decade. It is thus important that studies of adaptive governance take steps to contextualize their findings within the local political climate.

Climate change is one of the most critical problems of our time. I use content analysis and network analysis to critically examine corporate responses to climate change as they are outlined on the websites of three of Canada’s largest corporations: Suncor Energy, Royal Bank of Canada and Bell Canada. I consider the data in light of two theoretical perspectives: ecological modernization and eco-socialism. The primary research question is: is private environmental governance effectively addressing climate change? To answer this question I first consider two more rudimentary research questions. (1) How are Canadian corporations responding to climate change? (2) What kinds of private environmental governance are Canadian corporations engaging with? None of the private environmental governance initiatives in this study appear to be directly leading corporations to reduce GHG emissions. The three corporations are responding to climate change in ways determined by corporate needs, rather than what is necessary to mitigate climate change. / Graduate / 0626 / 0615 / eyles@uvic.ca

This case study examined the spread of ideas in a Gr. 5/6 classroom in which the teacher was attempting to foster a knowledge building community. The goal of the research was to explore the relationship between the social network of the classroom (in terms of face-to-face and computer-mediated interactions), the teacher’s role, and the spread of ideas. Further, the thesis examined how social network tools may help teachers better understand the pedagogical implications of Scardamalia and Bereiter’s (1991) Teacher A, B, C models. Analyses of videotaped lessons revealed the teacher used a complex mix of traditional instructional methods and knowledge building strategies while trying to shift the locus of control of learning to students. Critical teacher-driven processes included the class-wide adoption of knowledge building vocabulary and practices, and efforts to foster higher levels of student-student discourse. Analyses of online interactions provided strong evidence of highly interconnected student-student online networks, with the note reading network being especially dense. Longitudinal studies revealed these network established themselves early in the unit, and persisted during the course of the inquiry. There was evidence that idea improvement was present in addition to idea spread. In face-to-face classroom communication, the teacher’s role was more central, particularly in "Knowledge Building Talk" sessions. However, here too, the teacher made efforts to shift the locus of control. Overall the analyses suggest that social network tools are potentially useful for helping teachers make the difficult transition from "Teacher A" and "Teacher B" strategies, in which the locus of control is with the teacher, to "Teacher C" strategies, in which strategic cognitive processes are turned over to students. This dissertation proposes that movement toward Teacher C practices may be illustrated, in part, by a shift in classroom network topologies from that of a star-shaped network, centered on the teacher, to a highly interconnected student-student network. Finally, the thesis recounts a number of ways in which the use of social network tools uncovered discourse patterns of which the teacher was unaware, including gender differences in reading, building-on, and contribution patterns.

Statistical analysis of network data is an active field of study, in which researchers inves- tigate graph-theoretic concepts and various probability models that explain the behaviour of real networks. This thesis attempts to combine two of these concepts: an exponential random graph and a centrality index. Exponential random graphs comprise the most useful class of probability models for network data. These models often require the assumption of a complex dependence structure, which creates certain difficulties in the estimation of unknown model parameters. However, in the context of dynamic networks the exponential random graph model provides the opportunity to incorporate a complex network structure such as centrality without the usual drawbacks associated with parameter estimation. The thesis employs this idea by proposing probability models that are equivalent to the logistic regression models and that can be used to explain behaviour of both static and dynamic networks.