Fighting Food Waste With Portion Sizes

Problem Statement: The US wastes nearly 40% of our food, creating 125-160 billion pounds of waste annually, leading to high emission rates, resource depletion, and food insecurity. Research Question: What are the most effective waste mitigation and management strategies in the restaurant industry that could be utilized to produce a more sustainable environment? A survey administered on campus to classmates to investigate habits, behaviors, knowledge, and potential solutions around food waste yielded significant differences in how much of a meal was thrown out between fast food restaurants, full service restaurants, and buffets. While 25% of respondents throw out 11% or more of their meal at fast food restaurants, the amount of respondents throwing out 11% or more of their meal swells to 37% at full service restaurants. Asked why they throw this food out the most common responses included: Too large portions, ordering too much, inconsistent appetite, and leftovers brought home being thrown out. We deduce the differences are due to one size fits all plates, which are typically over the recommended calorie count. While a variation of small, medium and large sizes are often offered at fast food restaurants, no such options exist at full service restaurants. Males said the portion size of their meal correlated to their appetite 69% of the time but females said the correlation only occurred 57% of the time. Presented with various food waste mitigation strategies respondents were most in favor of the idea of customized menus with multiple portion options. 92% of respondents said they were at least somewhat likely to purchase a smaller portion for less cost. Meanwhile, 55% of respondents are somewhat likely to order smaller food portions for the identical price of the larger meal. Therefor in order to reduce food waste we propose implementing multiple portion options at restaurants.

Catch the Pig! Understanding Interaction Between People and AI
Our study sought to investigate the ways in which people would interact with an AI agent, based on how the agent was racialized. To investigate this we modeled a game after the stag hunt task, where participants were tasked with gaining as many points as possible. Participants could gain points by either cooperating with an AI agent to capture a pink game piece, which represented a pig or exiting the game through the black squares on either side of the board. The study was a true experiment in which participants were randomly assigned to one of three conditions. Participants were either assigned to a condition where the AI was racialized as Black, where the AI was racialized as white, or a condition where the AI wasn’t racialized at all, which represented the control condition. After completing the game participants were asked three survey questions to assess how they perceived the AI’s strategy when playing the game. So far our results have shown that participants in the control condition were more likely to believe the AI was working with them to capture the pig than participants in both the Black and white treatment groups. Moreover, the participants in the white treatment group were more likely than those in the Black treatment group to believe the AI agent was working them to capture the pig. The results do suggest that there is a relationship between the racialization, or lack thereof, of AI and how people interact with AI Agents.

Does Global Trade Help of Hinder Economic Equality?

The issue of globalization and its perceived winners and losers has recently come to the forefront of international conversation. In this project, we seek to answer the following question: has global trade helped decrease economic inequality? To address this problem, we created a tool that could be used to quantify the effect of global trade over time. Using a graph-theoretical approach, we adapt the Page Rank algorithm to account for a country’s importance in the trade network when considering financial flows that go in both directions, that is, both exports and imports. We then use the relative importance scores to quantify the economic inequality by computing the Gini coefficient of the world’s economy, as well as the associated Lorenz curve. By measuring the evolution of the Gini coefficient over time, we can estimate whether international trade helped or hindered addressing economic inequality among the participants in the global trade network.

Dissociating Socioeconomic Influences on Maternal Language Input and Child Language Outcomes

Early language development is associated with children’s socioeconomic status (SES). Specifically, children from lower SES backgrounds, on average, exhibit slower language development compared to their peers from higher-SES backgrounds. Even though SES is a multidimensional construct, research often relies on a single dimension or a composite measure when studying child language development. In this article, I investigate four dimensions of SES, including maternal education, income-to-needs ratio, financial security, and neighborhood SES. Specifically, I examine whether the quantity and quality of maternal linguistic input mediates the relationships between dimensions of SES and child receptive language skills. Mothers and their 36-40 months old children (n=276 dyads) were video recorded during a 15-minute free play session. Three measures of maternal linguistic input were derived from verbatim transcripts, including one quantitative measure (number of words spoken) and two qualitative measures (lexical diversity and syntactic complexity). Children’s concurrent receptive language skills were measured by a standardized measure of children’s ability to receive, process, and execute oral instructions of increasing syntactic complexity. Results revealed that maternal education was the strongest predictor of both maternal linguistic input and child receptive language outcomes. Syntactic complexity of input was the only measure that mediated the relationship between maternal education and child receptive language skills. These findings critically identify which early environmental factors are mechanistically related to SES disparities in children’s language development and provide implications for interventions to reduce these disparities.

A Study of Teacherpreneurs Who Create Elementary Mathematics Curricular Resources

Online teacherpreneurs are teachers who use social media platforms to create, sell, and distribute educational resources to others. For many teachers, they have become the new curriculum developers in our virtually intensive world, but little is known about these teacherpreneurs. Therefore, as part of a larger study investigating the top 1000 elementary mathematics educational resources found on TeachersPayTeachers.com (TpT), I have sought to learn more about the teacherpreneurs who created these top resources. From their TpT pages, I have recorded each teacherpreneurs’ teaching experiences, their educational background, what state or country they are from, the number of followers they have and how they market their resources. I compare this information to the number of their resources that are in the top 1000 and if they charge for these resources or not. Results show most teacherpreneurs have previous teaching experience with 18.7% reporting more than 20 years of teaching experience. The average number of followers for these teacherpreneurs is 15247 with 23.6% having more than 20,000 followers; this points to the popularity of these teacherpreneurs and leads to questions about how they promote themselves on social media. Results show that teacherpreneurs who promote themselves on 3 to 4 social media accounts and who are not currently teaching have higher follower counts.

Chinese International Students in the US: The Influence of Discrimination, Acculturation and Coping on Psychological Wellbeing

Chinese international students have been reported to experience psychological distress, help-seeking stigma, language-based discrimination, and acculturative stress. This study aims to investigate the influence of discrimination, acculturation and coping strategies on Chinese international students’ psychological wellbeing. With the increasing number of international students in the United States, the focus on their mental health is never greater.

Decision 2020: Rural Pennsylvania

The 2020 election was a point of inflection for Democratic candidates across the United States. Securing tossup states like Pennsylvania and Arizona along with parts of the industrial Midwest, the performance of Joe Biden and other down ballot candidates raises serious questions about the future of the Democratic Party. In particular, the geographic distribution of voters in the 2020 election surprised many in election-watching circles.

While many have analyzed Biden’s over-performance in suburbia and underperformance with Hispanics in Texas and Florida, few have attempted to break down the results of the election in rural Pennsylvania. Because it is at such a unique intersection of the class, race, and conservative-liberal divide, understanding the rural election results is crucial to developing strategies for improving Democratic performance in the Midwest and South.

As the Campaign Manager for a Democrat in 85th District of Pennsylvania (Lewisburg, Selinsgrove, Mifflinburg), I had the opportunity to interact with thousands of voters and develop strategies to improve outcomes in a R +32 district. The statewide data tells us that the 2020 election in Pennsylvania was, as local organizer Jordi Comas coined, an example of the “choppy purple surf.” In other words, the Republican turnout was unusually large, but slightly over-crested by Democratic voter turnout.

I will review the results of the election for my campaign in both a historical and geographical context and answer the question, “how did the ‘choppy purple surf’ play out in the the 85th District and other parts of rural Pennsylvania?