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This presentation illustrates the connections between the development of AI and modern neuroscience for a novice audience. I believe by studying these two multidisciplinary topics, we will gain a mindful understanding of how we learn, develop ways for encoding for context and biases, and be closer positioned to true artificial general intelligence.
Proposal for a digital toolkit aimed at youth delegates in NYC’s Participatory Budgeting process, in support of youth civic engagement. The toolkit reflects Connected Learning principles to encourage youth participation, and supports public librarians who volunteer as facilitators and make their branches “home bases” for youth committee meetings and collaboration.
NYPL obtained an enormous collection of digital materials on CD-R, and implemented a batch transfer process to ingest the materials. The batch transfer process obscured the success rate of the transfers; I analyzed metadata about the transferred materials to determine the success rate and improve the process.
Through a review of trends in the current literature on the topic, I explore community archives as an alternative to traditional archival practice. Ultimately, I argue for a reconceptualization of community archives as part of the archival continuum rather than as traditional or mainstream archives’ binary opposite.
Using Tableau Public and a series of datasets, this dashboard uniquely examines the phenomenon of concerning experiences online, with a feminist analytical framework. Gender dimensions are highlighted throughout, and gaps in available information is discussed. It is part of a larger series on online violence against women in politics.
This project discusses the development of an educational conversation agent supporting an initiative I developed called WESTAND, standing for We Emerge Stronger Together And Never Defenseless. The initiative and the agent serves to increase the accessibility of bystander intervention training–offered at no cost by some non-profit organizations but with limited capacity or in B2B settings.
This map, made in Carto, is an exploration of the relationship between public space and public housing in NYC. By examining the area and frequency of these dynamics within Community Districts, I illustrate the stark differences in NYC’s realized development priorities, highlighting impact on a hyperlocal scale in novel ways.
This presentation will showcase my work as the 2020-2021 Born-Digital Archives Fellow at the Guggenheim Museum Archives. It will highlight the project evolution of appraising a backlog of curatorial records to uploading exhibition assets to a digital asset management system for museum-wide discovery.
This presentation addresses ethical issues concerning youth participation within the process of selecting for children’s collections. It examines current practices in the Collection Development/Selection Policies of school libraries nationwide through the lens of children’s rights (defined by the UN Convention of the Child) and proposes youth-inclusive approaches.
This presentation introduces some primary research paradigms with an emphasis on the UX field. By introducing the philosophical assumptions behind those paradigms, this presentation also introduces a way to evaluate a research design.
I will present a data analysis project in which I use basic machine learning to analyze the types of Trump voters and how the groups differ from one another in their opinions on various political issues. A summary of the project is available here: https://wmerrow.github.io/work/types-trump-voters.html
This project originated with Professor Lopatovska’s Info 601 class, in which I analyzed and wrote a paper about do-it-yourself music archives as an alternative method of archival preservation. I will define DIY in relation to community archives, explain the importance of DIY music archives and problems that they face.
Using various GIS and Census Bureau data, this project explores different map formats showing the relationship between race and poverty in seven Hudson River communities. The aim is to create a more human, almost impressionistic visualization of a kind of data that we have seen countless times before.