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Negotiating Narratives of Canada: Circuit of Communication Analysis of the Next Stop Freedom Exhibition
Museums and historic sites in Canada are public places of representation and social encounters where Canadians present, express, and confirm cultural identities and community belonging. Narratives of identity in these heritage institutions are under pressure to change to reflect Canadian society as it diversifies. This essay examines a particular case where African Canadians joined a collaborative process with the federal agency Parks Canada and the Ontario Black History Society to create one of Parks Canada’s first exhibitions on Black history, presented in 2002-2005. The research project studied the exhibit’s circuit of communication—the debates around the production of the historical narrative, the exhibition itself as a cultural text, and the varied reception of the exhibition by visitors. The study found complex negotiation of narratives of Canada behind the scenes, but a mainstreaming effect inherent within the exhibit design and a lack of new or transformative understandings by most viewers. The analysis suggests a lack of bridging between the processes of production and reception due to the limitations of the exhibit form itself.
Journal Article
Analysis of Latent Space Representations for Object Detection
Deep Neural Networks (DNNs) successfully perform object detection tasks, and the Con- volutional Neural Network (CNN) backbone is a commonly used feature extractor before secondary tasks such as detection, classification, or segmentation. In a DNN model, the relationship between the features learned by the model from the training data and the features leveraged by the model during test and deployment has motivated the area of feature interpretability studies. The work presented here applies equally to white-box and black-box models and to any DNN architecture. The metrics developed do not require any information beyond the feature vector generated by the feature extraction backbone. These methods are therefore the first methods capable of estimating black-box model robustness in terms of latent space complexity and the first methods capable of examining feature representations in the latent space of black box models.This work contributes the following four novel methodologies and results. First, a method for quantifying the invariance and/or equivariance of a model using the training data shows that the representation of a feature in the model impacts model performance. Second, a method for quantifying an observed domain gap in a dataset using the latent feature vectors of an object detection model is paired with pixel-level augmentation techniques to close the gap between real and synthetic data. This results in an improvement in the model’s F1 score on a test set of outliers from 0.5 to 0.9. Third, a method for visualizing and quantifying similarities of the latent manifolds of two black-box models is used to correlate similar feature representation with increase success in the transferability of gradient-based attacks. Finally, a method for examining the global complexity of decision boundaries in black-box models is presented, where more complex decision boundaries are shown to correlate with increased model robustness to gradient-based and random attacks.
Dissertation
Knowledge development in early childhood : sources of learning and classroom implications
\"Synthesizing cutting-edge research from multiple disciplines, this book explores how young children acquire knowledge in the \"real world\" and describes practical applications for early childhood classrooms. The breadth and depth of a child's knowledge base are important predictors of later literacy development and academic achievement. Leading scholars describe the processes by which preschoolers and primary-grade students acquire knowledge through firsthand experiences, play, interactions with parents and teachers, storybooks, and a range of media. Chapters on exemplary instructional strategies vividly show what teachers can do to build children's content knowledge while also promoting core literacy skills\"-- Provided by publisher.
Book
Trading between architecture and art : strategies and practices of exchange
Since the 1960s, art and architecture have experienced a series of radical and reciprocal trades. Just as artists have simulated \"architectural\" means like plans and models, built structures and pavilions, or intervened in urban and public spaces, architects have employed \"artistic\" strategies in art institutions, exhibitions, and more. Likewise, art galleries and museums have combined both activities, playing with the conditional differences between inside and outside the institutions. This book focuses on specific case studies of these two-way, interdisciplinary transactions. Included are texts and visual essays by Mark Dorrian, Rosemary Willink, Sarah Oppenheimer, and many others.
Book
Seeking Real Truths: Multidisciplinary Perspectives on Machiavelli
The thought and influence of Machiavelli have had a significant impact on a variety of academic disciplines, including political science and government, history, literature, language, theatre, and philosophy. Rather than inscribe Machiavelli within the boundaries of a single academic approach, tradition, or discourse, this volume assembles multidisciplinary perspectives on his writings on government, on his creative works, and on his legacy. The result is intended to appeal at once to generalists seeking baseline knowledge of Machiavelli and to specialists who are interested in critical views of Machiavelli that use a broad lens and that approach their subject from different angles.Contributors include: Susan Ashley, Salvatore Bizzarro, Julia Bondanella, JoAnn Cavallo, Salvatore Di Maria, Marie Gaille-Nikodimov, Eugene Garver, Joseph Khoury, William Klein, Sante Matteo, Gerry Milligan, RoseAnna Mueller, John Roe, Gerald Seaman, Charles Tarlton, Patricia Vilches, and Mary Walsh.
eBook
Build-A-Code: Design and Evaluation of a Tool for Helping Novice Programmers Learn New APIs
Application Programming Interface, or API, learning has become an integral part of becoming a proficient and modern programmer. In particular, API learning is necessary for a programmer to advance beyond a novice skill level rather than naively copying code from the internet. Learning an API, however, presents many challenges, especially in the area of making API documentation and examples more readily useful and understandable to the novice programmer. Our preliminary idea is that by making information about APIs within examples easier to understand and access, the programmer will learn more about the API compared to simply copying and pasting the examples. In this thesis we built the Atom Clipboard History tool and did a preliminary evaluation to test the usefulness of this tool. Considering the user study and cognitive walkthrough for this tool together, we can conclude most of the study users would find the Atom History Clipboard tool to be useful.
Dissertation