Social and Behavioral Sciences Commons^™

Discourse, Power Dynamics, And Risk Amplification In Disaster Risk Management In Canada, Martins Oluwole Olu-Omotayo

Electronic Thesis and Dissertation Repository

The domain of disaster risk management is rife with discursive contentions, whereby dominant discourses amplify the powers of risk actors to precipitate and reinforce political, economic, and environmental inequalities that predispose different sections of the population to unequal disaster risk vulnerabilities. This thesis identified important actors (government, risk experts, media, and NGOs) that shape the power dynamics in disaster risk management in Canada and explained their roles, influences, and the dimensions in which their powers negotiate each other through risk discourses. The patterns of these power dynamics in the three aspects of power –communication, assessment, and social trust –were also …

Safe Sharing For Sensitive Data, Kristi Thompson

Western Libraries Presentations

This workshop focused on the question of when and how human subjects' data can be safely shared. It introduced the basics of data anonymization and discussed how to tell if a dataset has been de-identified. Case studies of successful anonymization and some spectacular failures were shared

Getting Started Analyzing Data In Spss, Kristi Thompson

Western Libraries Presentations

SPSS is a popular package for analyzing data. This session will discuss how to get started on a simple quantitative analysis project using SPSS. Topics covered will include getting summary statistics, creating and modifying variables, creating graphs, running simple analyses, and interpreting SPSS output.

Statistical Roles Of The G-Expectation Framework In Model Uncertainty: The Semi-G-Structure As A Stepping Stone, Yifan Li

Electronic Thesis and Dissertation Repository

The G-expectation framework is a generalization of the classical probability system based on the sublinear expectation to deal with phenomena that cannot be described by a single probabilistic model. These phenomena are closely related to the long-existing concern about model uncertainty in statistics. However, the distributions and independence in the G-framework are quite different from the classical setup. These distinctions bring difficulty when applying the idea of this framework to general statistical practice. Therefore, a fundamental and unavoidable problem is how to better understand G-version concepts from a statistical perspective.

To explore this problem, this thesis establishes a new substructure …

Cnn-Lstm Vs Ann: Option Pricing Theory, Edward Chang

Undergraduate Student Research Internships Conference

The modern derivatives market has been steadily growing since the development of the first accurate option pricing model by Fischer Black, Robert Merton, and Myron Scholes. Since then, there have been many different approaches to more accurately price options like the binomial option pricing model and approaches using technology such as machine learning. There are many different research papers on option pricing with artificial neural networks (“ANN”) but not many with other neural network types. We contribute to the existing literature by developing a convolutional neural network – long short-term memory (“CNN-LSTM”) model to price options and compare it to …

A Qualitative Look Into Repair Practices, Jumana Labib

Undergraduate Student Research Internships Conference

This research poster is based on a working research paper which moves beyond the traditional scope of repair and examines the Right to Repair movement from a smaller, more personal lens by detailing the 6 categorical impediments as dubbed by Dr. Alissa Centivany (design, law, economic/business strategy, material asymmetry, informational asymmetry, and social impediments) have continuously inhibited repair and affected repair practices, which has consequently had larger implications (environmental, economic, social, etc.) on ourselves, our objects, and our world. The poster builds upon my research from last year (see "The Right to Repair: (Re)building a better future"), this time pulling …

Simulating Salience: Developing A Model Of Choice In The Visual Coordination Game, Adib Sedig

Undergraduate Student Research Internships Conference

This project is primarily inspired by three papers: Colin Camerer and Xiaomin Li’s (2019 working paper)—Using Visual Salience in Empirical Game Theory, Ryan Oprea’s (2020)—What Makes a Rule Complex?, and Caplin et. al.’s (2011)—Search and Satisficing. Over the summer, I worked towards constructing a model of choice for the visual coordination game that can model player behavior more accurately than traditional game theoretic predictions. It attempts to do so by incorporating a degree of bias towards salience into a cellular automaton search algorithm and utilizing it alongside a sequential search mechanism of satisficing. This …

Differentiating Fissure-Fed Lava Flow Types And Facies Using Radar And Lidar: An Example From The 2014–2015 Holuhraun Lava Flow-Field, Gavin Douglas Tolometti, Catherine D. Neish, Christopher W. Hamilton, Gordon R. Osinski, Antero Kukko, Joana R.C. Voigt

Earth Sciences Publications

Distinguishing between lava types and facies using remote sensing data is important for interpreting the emplacement history of lava flow-fields on Earth and other planetary bodies. Lava facies typically include a mixture of lava types and record the collective emplacement history of material preserved at a particular location. We seek to determine if lava facies in the 2014–2015 Holuhraun lava flow-field are discernible using radar roughness analysis. Furthermore, we also seek to distinguish between lava types using high resolution Light Detection and Ranging (LiDAR) data. We extracted circular polarization ratios (CPR) from the Uninhabited Aerial Vehicle Synthetic Aperture Radar and …

Understanding The Enumerated World: Making Sense Of Data As An Information Source, Kristi Thompson, Elizabeth Hill, Alexandra Cooper

Western Libraries Publications

Chapter in ACRL publication The Data Literacy Cookbook.

This recipe is a guide to preparing an instructional session aimed at postsecondary students in the social or health sciences or related disciplines on locating, evaluating, and using secondary data sources as information resources. Who collects data? Where can you access them? Why are data available on some topics and not others? Why are some statistics available at a detailed level of geography and others only nationally? What are some key limitations of official statistics, and where can information be found to fill in the gaps? This recipe uses these questions to …