This thesis responds to the question, "Can Science Make Sense of Life?" through a structural lens of the Human Germline Genetic Editing debate. I explore who is absent from the table, and how the ways of thinking that dominate marginalize and exclude alternative frameworks and considerations. This analysis is centered around an examination of several perspectives from the disability community and an in-depth study of how the Orthodox Jewish community contends with genetic disease. These perspectives illuminate several lessons that prove to bring insight not merely to questions of permissibility on genetic editing, but also offer reflections on the larger relationship between science, technology, and society. I then return to the mainstream genetic editing debate to show how the culture it is born out of and the structures it has ingrained prevent lessons such as these from impacting the conversation. In light of such structures that continuously reproduce the assertion that it is science, not humanity, that is able to make sense of life, my final argument is that though science tends to gatekeep questions of emerging technologies by centering conversations on highly advanced and methodological considerations, public individuals need not feel as if they are irrelevant or unessential. Though science may offer one solution, it is the individuals and communities, not results from a lab, that are equipped to determine if it is the best solution.

Surveys have shown that several hundred billion weather forecasts are obtained by the United States public each year, and that weather news is one of the most consumed topics in the media. This indicates that the forecast provides information that is significant to the public, and that the public utilizes details associated with it to inform aspects of their life. Phoenix, Arizona is a dry, desert region that experiences a monsoon season and extreme heat. How then, does the weather forecast influence the way Phoenix residents make decisions? This paper aims to draw connections between the weather forecast, decision making, and people who live in a desert environment. To do this, a ten-minute survey was deployed through Amazon Mechanical Turk (MTurk) in which 379 respondents were targeted. The survey asks 45 multiple choice and ranking questions categorized into four sections: obtainment of the forecast, forecast variables of interest, informed decision making based on unique weather variables, and demographics. This research illuminates how residents in the Phoenix metropolitan area use the local weather forecast for decision-making on daily activities, and the main meteorological factors that drive those decisions.

As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).