12 resultados para ACTOR-NETWORK

em Brock University, Canada


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This thesis undertakes an exploration of the nature of alternative food projects in Niagara. A review of various theoretical approaches to the study of food and agriculture, suggests that actor-network theory offers the most useful lens through which to understand these projects. In particular, actor-network theory facilitates non-dualistic theorisations of power and scale and a commitment to the inclusion of non-humans in the 'social' sciences. The research is based on 19 in-depth interviews with actors involved in various urban and rural projects including community supported agriculture, community gardens, chefs using local seasonal food, a winery that grows organically, the good food box, a value-added small business, and organic producers. The analysis consists of four themes. The first analytical section pays special attention to the prominence of agri-tourism in Niagara, and examines the ways in which the projects in the sample interact with agri-tourist networks. In the second section the discussion focuses on the discourses and practices of resistance among Niagara alternative food actors. The participants' interviews suggest there are more discourses of resistance toward agri-tourist than toward dominant food networks. The third section questions commodity chain theorisations of alternative food projects. In particular, this section shows how the inclusion of non-human actors in an analysis confounds conceptualisations of 'short' and 'local' chains. The final analytical section assesses relations of power in Niagara alternative food projects. Three important conclusions arise from this research. First, Niagara alternative food projects cannot be conceptualised as operating at the 'local' scale. Broadening the scope of analysis to include non-human actors, it becomes apparent that these projects actually draw on a variety of extra-local actors. They are at once local and global. Second, the projects in this sample are simultaneously part of alternative, dominant and agri-tourist networks. While Niagara alternative food projects do perform many of the roles characteristic of alternative food systems, they are also involved in practices of development, business, and class distinction. Thus, alternative food networks should not be understood as separate from and in direct opposition to dominant food networks. Despite the second conclusion, this research determines that Niagara alternative food projects have made significant strides in the reworking of power. The projects represented in this thesis do engage in resistant practices and are associated with increased levels ofjustice.

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A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

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The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.

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Warren Hartman was born in 1942 in Toronto, Ontario. He received a B.A. in Fine Arts and Drama from Brock University in 1981 and a Masters of Arts in Humanities at the State University of New York at Buffalo in 1987. In the 1950s he did considerable work as a child-actor both in theatre and television. From 1953 to 1961 he was in the New Play Society under the direction of Dora Mavor Moore. His last two years there were spent as a scholarship student. From 1963 to 1966 he did an apprenticeship with Suzanne Mess, Head of Costume Design at The Canadian Opera Company in Toronto. In 1976 Warren attended a Master Class in Scenography at the Banff School of Fine Arts with Josef Svoboda. In the spring of 1970 Warren was a guest designer at Brock University and from 1970 to 1972 he remained at Brock as resident designer and special lecturer. During this time he was also an instructor and costume designer at Sheridan College in Oakville. It was in 1972 that he became the designer-in-residence at Brock University. From 1984 he held the position of Associate Professor at The Department of Fine Arts at Brock University until the fall of 1996. Some of the highlights of Warren’s career also include: stage managager with the Street Hat Players in Port Carling, Ontario, 1960-1961; a freelance designer for over 100 shows; costume coordinator(production manager) for the Canadian Opera Company, 1964 -1970; resident costume designer for The Canadian Opera Company, 1965- 1970; founder and artistic director of Dei Gelosi Campagnia, St.Catharines, Ontario, 1970-1973; freelance director of some thirty-five shows; co-producer for Quebec City Summer Stock Company, Quebec City, Quebec, 1975; a consultant with Alberta Culture for the Provincial Government of Alberta, 1986-1987 and associate artistic director at Theatre Network, Edmonton, Alberta, 1986-1987. Warren Hartman was the recipient of the Jean Chalmers Award for contributions to Canadian Theatre for persons 25 years of age or under, in 1965. He was a founding member of Associated Designers of Canada and was affiliated with Canadian Actors Equity. Warren Hartman died on Feb. 11, 1998 several days after suffering a massive stroke. A memorial service was held at Brock University in May of 1998 and a bursary fund was established in his name.

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The individual and dyadic associations between dispositional forgiveness of self, others, and situations and mental and physical health in individuals involved in romantic relationships were examined. Sex differences in the relationship between dispositional forgiveness and health were examined. Sex differences in the dyadic relationship between forgiveness and health were also examined. The dispositional forgiveness scores of 297 partners involved in a romantic relationship were used to predict their own as well as their partners' physical and mental health. Both members of the relationship separately completed an Internet-based questionnaire assessing personality traits, relationship variables, and physical and mental health. The couple was provided with monetary compensation. Analyses revealed that women's dispositional forgiveness of self, others, and situations were positively associated with their own physical and mental health. Similarly, men's dispositional forgiveness of self, others, and situations were positively associated with their own mental and physical health. At the individual level, there were no sex differences in the relationship between dispositional forgiveness and health, nor were there sex differences in men and women's reports of dispositional forgiveness. Analyses revealed that men's forgiveness of others and situations were positively associated with their female partners' mental health. There were no partner effects for women or for physical health. The implications of these results for research in the forgiveness-health literature and research on forgiveness in romantic relationships were discussed as were directions for future research.

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While service-learning is often said to be beneficial for all those involved—students, community members, higher education institutions, and faculty members—there are relatively few studies of the attraction to, and effect of, service-learning on faculty members. Existing studies have tended to use a survey design, and to be based in the United States. There is a lack of information on faculty experiences with service-learning in Ontario or Canada. This qualitative case study of faculty experiences with service-learning was framed through an Appreciative Inquiry social constructionist approach. The data were drawn from interviews with 18 faculty members who belong to a Food Security Research Network (FSRN) at a university in northern Ontario, reports submitted by the network, and personal observation of a selection of network-related events. This dissertation study revealed how involvement with service-learning created opportunities for faculty learning and growth. The focus on food security and a commitment to the sustainability of local food production was found to be an ongoing attraction to service-learning and a means to engage in and integrate research and teaching on matters of personal and professional importance to these faculty members. The dissertation concludes with a discussion of the FSRN’s model and the perceived value of a themed, transdisciplinary approach to service-learning. This study highlights promising practices for involving faculty in service-learning and, in keeping with an Appreciative Inquiry approach, depicts a view of faculty work at its best.

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The purpose of this study was to understand referral linkages that exist among falls prevention agencies in a southern Ontario region using network analysis theory. This was a single case study which included fifteen individual interviews. The data was analyzed through the constant comparative approach. Ten themes emerged and are classified into internal and external factors. Themes associated with internal factors are: 1) health professionals initiating services; 2) communication strategies; 3) formal partnerships; 4) trust; 5) program awareness; and 6) referral policies. Themes associated with external factors are: 1) client characteristics; 2) primary and community care collaboration; 3) networking; and 4) funding. Recommendations to improve the referral pathway are: 1) electronic database; 2) electronic referral forms; 3) educating office staff; and 4) education days. This study outlined the benefit of using network analysis to understand referral pathways and the importance of implementing strategies that will improve falls prevention referral pathways.

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We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these networks. On the other hand, it is natural to seek for game-theoretic network formation models in which links are formed due to strategic behaviors of individuals, rather than based on probabilities. Inspired by Even-Dar and Kearns (2007), we consider a more realistic model in which the cost of establishing each link is dynamically determined during the course of the game. Moreover, players are allowed to put transfer payments on the formation of links. Also, they must pay a maintenance cost to sustain their direct links during the game. We show that there is a small diameter of at most 4 in the general set of equilibrium networks in our model. Unlike earlier model, not only the existence of equilibrium networks is guaranteed in our model, but also these networks coincide with the outcomes of pairwise Nash equilibrium in network formation. Furthermore, we provide a network formation simulation that generates small-world networks. We also analyze the impact of locating players in a hierarchical structure by constructing a strategic model, where a complete b-ary tree is the seed network.

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A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

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In this thesis, I focus on supply chain risk related ambiguity, which represents the ambiguities firms exhibit in recognizing, assessing, and responding to supply chain disruptions. I, primarily, argue that ambiguities associated with recognizing and responding to supply chain risk are information gathering and processing problems. Guided by the theoretical perspective of bounded rationality, I propose a typology of supply chain risk related ambiguity with four distinct dimensions. I, also, argue that the major contributor to risk related ambiguity is often the environment, specifically the web of suppliers. Hence, I focus on the characteristics of these supplier networks to examine the sources of ambiguity. I define three distinct elements of network embeddedness – relational, structural, and positional embeddedness – and argue that the ambiguity faced by a firm in appropriately identifying the nature or impacts of major disruptions is a function of these network properties. Based on a survey of large North American manufacturing firms, I found that the extent of the relational ties a firm has and its position in the network are significantly related to supply chain risk related ambiguity. However, this study did not provide any significant support for the hypothesized relationship between structural embeddedness and ambiguity. My research contributes towards the study of supply chain disruptions by using the idea of bounded rationality to understand supply chain risk related ambiguity and by providing evidence that the structure of supply chain networks influences the organizational understanding of and responses to supply chain disruptions.

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Consistent with the governance shift towards network forms of governance, a number of new social movements have formed in response to the declining levels of physical activity in the Western world. One such movement is Active Canada 20/20: A Physical Activity Strategy and Change Agenda for Canada. Network governance is employed as the theoretical framework for this case study exploration of Active Canada 20/20 and the political landscape surrounding its development and implementation. Semi-structured interviews were conducted in addition to document/policy analysis and direct observations. Analysis of the data resulted in three overarching themes – the defining characteristics of network governance, the political landscape, and intersectoral linkages – that interconnect multifariously based the nature of the Canadian federal government and its relationship with the voluntary sector for physical activity. Despite progress in driving Active Canada 20/20 forward, entrenched dynamics of power need to be navigated within the political landscape surrounding network governance.

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The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.