Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.

Educational Technology Decision-Making: A Case Study on Technology Acquisition for 746,000 Ontario Students

Very little research has examined K–12 educational technology decision-making in Canada. This collective case study explores the technology procurement process in Ontario’s publicly funded school districts to determine if it is informed by the relevant research, grounded in best practices, and enhances student learning. Using a qualitative approach, 10 senior leaders (i.e., chief information officers, superintendents, etc.) were interviewed. A combination of open-ended and closed-ended questions were used to reveal the most important factors driving technology acquisition, research support, governance procedures, data use, and assessment and return on investment (ROI) measures utilized by school districts in their implementation of educational technology. After participants were interviewed, the data were transcribed, member checked, and then submitted to “Computer-assisted NCT analysis” (Friese, 2014) using ATLAS.ti. The findings show that senior leaders are making acquisitions that are not aligned with current scholarship and not with student learning as the focus. It was also determined that districts struggle to use data-driven decision-making to support the governance of educational technology spending. Finally, the results showed that districts do not have effective assessment measures in place to determine the efficacy or ROI of a purchased technology. Although data are limited to the responses of 10 senior leaders, findings represent the technology leadership for approximately 746,000 Ontario students. The study is meant to serve as an informative resource for senior leaders and presents strategic and research-validated approaches to technology procurement. Further, the study has the potential to refine technology decision-making, policies, and practices in K–12 education.

The Canada Not For Profit Corporations Act: Perceived impact on the governance of federal sport organizations

This thesis examined the impact of the Canada Not-for-Profit Corporations Act (2009) on the governance of national sport organizations (NSO). The impact of the legislation was explored through the perceptions of NSO executive leaders and by analyzing the by-laws in effect before the legislation. The legislation was perceived to have the greatest impact on enhancing accountability, specifically affecting membership categories and director selection. The interview data showed that the legislation was necessary to enhance accountability in many NSOs. The Respondents also demonstrated that they understood the goals sought through the legislation. The data also showed that the boards of NSOs were already in alignment with the goals of the legislation. With respect to governance, the data indicated that NSOs rely almost exclusively on their regional sport associations as voting stakeholders. An emerging issue that came out of the results was the role of athletes in the governance of sport organizations.

Resilience in a Watershed Governance Context: A Primer

Watersheds are complex systems involving social, economic, and ecological dimensions that are constantly interacting and influencing each other, and governance of these systems involve a large and diverse cast of actors that add to the complexity and difficulty in deciding what is best for the watershed and people. Resilience thinking offers a way to understand and navigate the uncertainty, dynamics and complexity of watershed governance. This primer describes key ideas associated with resilience: more inclusive participation; building a shared understanding; inclusion of ecosystem services and functions in long-term planning; strong leadership; institutional and decision making flexibility; and, a decentralized system. This primer is an initial effort to translate the scholarly understanding of these key ideas and initiate a dialogue about their application in the context of watershed governance.