Social Sciences – Page 18 – UROP Spring Symposium 2021

Social Sciences

Optimal Exchange-Rate Policy Under Collateral Constraints and Wage Rigidity Research Paper Presentation

Houston Scott Pronouns: He, Him, His Research Mentor(s): Pablo Ottonello, Assistant Professor Research Mentor School/College/Department: Economics, College of Literature, Science, and the Arts Presentation Date: Thursday, April 22, 2021 Session: Session 3 (1pm-1:50pm) Breakout Room: Room 4 Presenter: 4 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Houston […]

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Leader Career Narratives

Sarah Williams Pronouns: she/her/hers Research Mentor(s): Elizabeth Trinh, PhD Student Research Mentor School/College/Department: Management and Organizations, Ross School of Business Presentation Date: Thursday, April 22, 2021 Session: Session 3 (1pm-1:50pm) Breakout Room: Room 4 Presenter: 6 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Sarah Williams, Elizabeth Trinh,

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Leader Career Narratives

Emily Kagan Pronouns: She/Her Research Mentor(s): Elizabeth Trinh, PhD Student Research Mentor School/College/Department: Management and Organizations, Ross School of Business Presentation Date: Thursday, April 22, 2021 Session: Session 3 (1pm-1:50pm) Breakout Room: Room 4 Presenter: 7 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Emily Kagan, Elizabeth Trinh

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White employers’ evaluations of same-race referrals: The role of perceived in-group favoritism

Racial inequality and discrimination are still pervasive in the U.S. labor market. While prior research finds that employers discriminate against Black and Latino jobseekers without referrals, we know less about how race affects how employers evaluate jobseekers’ same-race referrals. This is important because many jobseekers find employment through referrals; these referrals are typically of the same race as the applicant. To address this gap in literature, we conducted a survey experiment where we tested the differences in how employers evaluate the same-race referrals of White, Black, Hispanic and Asian job applicants. The analyzed data come from an empirical experiment conducted in the United States. White individuals (n = 635) with hiring and/or supervisory experience in their workplace were recruited through Amazon Mechanical Turk to participate in a survey experiment. Respondents were assigned a random racial group (Black, White, Hispanic, Asian) and were asked whether individuals of these racial groups prefer to refer individuals of their same race, or the best qualified job applicants. Respondents were then asked to explain their choice in their own words and their responses were coded into a fairly small number of categories. We found that while approximately half of the sample stated that Black and Hispanic employees prefer to refer applicants of their same race than the “best qualified” applicants, and approximately 1/3 reported the same for Asian employees, only 16% stated that whites prefer to refer white applicants rather than the best-qualified applicants. This suggests white hiring agents are more likely to dismiss non-whites’ same-race referrals””seeing them as a reflecting in-group bias rather than credibly signaling applicant quality””than whites’ same-race referrals. We also analyze the open-ended responses to examine mechanisms underlying these racial differences.

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What Are People Thinking About the Elections and Other Political Topics?

The 2020 release of a story linking Hunter Biden, the son of then Presidential candidate Joe Biden, to corrupt business deals with Ukraine by the New York Post brought copious media attention to the Biden family. This study seeks to capture the sentiment of survey respondents between Hunter Biden and belief in a New York Post story. Despite the proliferation of textual survey analysis, the use of auditory data in survey collection is a relatively unexplored field. Further, we hypothesize that audio data provides a unique opportunity to detect belief among populations better than textual data. Using both the audio and textual responses from 1,000 survey respondents answering the open-ended question of “what, if anything, have you heard about Donald Trump and Joe Biden,” we can code for sentiment analysis: to detect sarcasm, irony, and tone to construct a clearer picture of actual opinion. The results showed a small effect in the difference of sentiment coded between the textual and oral responses. Through an analysis of the opinions, the survey respondents typically believed that the story had incriminated Joe Biden. These results suggest that the attitudes of survey respondents are accurately depicted through the textual-based responses.

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What Are People Thinking About the Elections and Other Political Topics?

The 2020 release of a story linking Hunter Biden, the son of then Presidential candidate Joe Biden, to corrupt business deals with Ukraine by the New York Post brought copious media attention to the Biden family. This study seeks to capture the sentiment of survey respondents between Hunter Biden and belief in a New York Post story. Despite the proliferation of textual survey analysis, the use of auditory data in survey collection is a relatively unexplored field. Further, we hypothesize that audio data provides a unique opportunity to detect belief among populations better than textual data. Using both the audio and textual responses from 1,000 survey respondents answering the open-ended question of “what, if anything, have you heard about Donald Trump and Joe Biden,” we can code for sentiment analysis: to detect sarcasm, irony, and tone to construct a clearer picture of actual opinion. The results showed a small effect in the difference of sentiment coded between the textual and oral responses. Through an analysis of the opinions, the survey respondents typically believed that the story had incriminated Joe Biden. These results suggest that the attitudes of survey respondents are accurately depicted through the textual-based responses.

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Quality Challengers in Senate Primary Elections, 1956-2020

Current research on U.S Senate elections has primarily been focused on general elections. Due to this, the project is expanding election research by examining primary elections and the factors that influence candidate emergence. In order to compile all of the primary election statistics, data was collected from CQ Voting Collections for each primary in all fifty states from 1956 to 2020. After information pertaining to the election was collected, such as the cote totals and percentages each candidate received, then categorical data were collected to help assess the quality of each challenger. Each Candidate’s occupation was collected from Newspapers.com and coded to signify their level of prior electoral experience. The data will be analyzed to assess the quality of each challenger and to examine the difference between amateur candidates and experienced candidates. This research will likely have implications on senatorial campaigns and experienced candidates. This research will likely have implications on senatorial campaigns and other features of senate races such as funding and election predictions.

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Quality Challengers in Senate Primary Elections, 1956-2020

Elections are an important trademark of just about every modern democracy and help to facilitate expressions of public opinion into the government. Because elections are an important part of democracy it makes sense to analyze them in order to better understand human behavior and electoral outcomes. Quite often elections are studied in order to try and predict how candidates perform in the election and possible reasons as to why they did as well as they did. One part that is often analyzed is the differences between quality and amateur candidates. This relationship has been examined for congressional primary elections, but has not been observed in regards to Senate primary elections. This study seeks to discover how being a quality challenger correlates with success in a senate primary election. Quality challengers are characterized by their previous political careers. Previous political experience, successfully running a campaign for elected office, separates quality challengers from their amateur counterparts. Success in a primary election is characterized by the percentage of votes they received, with the winning candidate receiving a majority of the vote. This methodology also takes into account other variables that may significantly affect results in Senate elections, for example the type of Senate primary election. In order to examine this relationship, different levels of political experience and non-political experience are given a number from 0-30 that indicates their level of quality. This number has 0 as the lowest indication of quality and 30 as the highest level of quality. This number is then attached to the candidate’s success in the election, and through Microsoft excel a correlation will be generated between success in elections and quality level. In the future, the information found in this study can hopefully be used to better understand how people vote and therefore able to effectively anticipate the results of future senate primary elections with moderate success.

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Quality Challengers in Senate Primary Elections, 1956-2020

“Quality Challengers in Senate Primary Elections,” examines U.S. Senate primary elections between 1956 to 2020. The focus of the study is on the extent to which quality challengers outperform amateur challengers. A quality challenger is an electoral candidate that has previous experience running in a government election. An amateur challenger is a candidate who has not had previous election experience. The project requires archival data collection of candidate’s backgrounds as well as election information specific to each candidate in order to complete the data set. The data collection involves accumulation of information from various websites pertaining to individual candidates and primary election information. For example, the following information is collected: the candidate’s name, the state, political party, number of candidates running in the election, the incumbent, total number of votes, candidate’s votes, percentage of votes, gender, type of primary, candidate’s party versus the incumbent’s party, quality challenger, and quality are variables of interest. Thus far, there has been a trend that people who have had previous election experience (quality challengers) also have more votes and a higher success rate in senate elections compared to those who had have no prior experience (amateurs). These data will be further analyzed to examine the differences between amateur candidates versus the quality challengers. This research has important implications for the selection of senatorial candidates, for campaign fundraising, and for campaign support of senatorial candidates.

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Parent Support for Selective Admissions Applications

For my research I worked in Parent Support for Selective Admissions Applications, assisting my mentor in various projects such as market research, application translation, and writing admission and denial letters. The central objective of my work was to create a more equitable admissions process that would be accessible to all regardless of socioeconomic status or other identifiers.

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