School of Humanities and Social Science Division of Social Science 224 Generations and Gender Survey Work Supervisor: GIETEL-BASTEN Stuart Arthur / SOSC Student: LAI Man Ting / RMBI NG Kai Yuen Dominic / QSA Course: UROP2100, Spring UROP2100, Spring We were involved in the conduct of the Hong Kong Generation and Gender Survey (HK-GGS). The HKGGS collects information of different generations, where the questions are related to daily lives such as interpersonal relationships, life satisfaction, gender roles and working environment. Our tasks were mainly focused on the preparatory activities – e.g., translating and localizing the survey questions, proofreading, beta testing and fixing errors of the online questionnaire, and preparing the invitation and reminder letters. Our involvement in these activities have improved our soft skills such as organization, communication and critical thinking skills. Some of the tasks required interacting with the other team members which greatly improved our interpersonal skills. We also gained a deeper understanding of how to run an online social survey. Our teamwork spirit has also been fostered through this project. Machine Learning for Processing Historical Images Supervisor: GIETEL-BASTEN Stuart Arthur / SOSC Student: SRIRAM Shriya / SENG Course: UROP1000, Summer Population figures can act as indicators for the living standards of people in certain areas at specific times. It reveals information about and observations on the differences among various groups in a society including but not limited to ethnicity, gender, and occupation. These differences can be effectively quantified and observed in the analysis of population statistics. In this project, we hoped to place our focus on the past and explore any important trends in the records of births and deaths that may inform us about potential inequalities faced by different population groups. Data on births and deaths in Wilmington, New Castle, United States from the late 1800s to the early 1900s was interpreted, transcribed, and studied. The most significant findings highlight that the birth and death rates may have been significantly impacted by social situations on race and the economy.
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