Youngjin Chae
Biographic Data
| ID | 188601 |
|---|---|
| NAME | Youngjin Chae |
| GIVEN NAMES | Youngjin |
| FAMILY NAME | Chae |
| SIGNATURE | CHAE Y |
| AFFILIATIONS | Rutgers, the State University of New Jersey |
| ORCID | 0000-0001-5074-9712 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
The effects of environmentalism on fertility in the United States
Environmental issues such as climate change have become major contemporary concerns that affect beliefs and, in some cases, behaviors. We examine whether and how environmentalism may have contributed to the second demographic transition that has driven declining fertility in some parts of the world since the 1970s. Data come from the 2006–2014 and 2016–2020 General Social Survey rolling panels in the USA. We fit Bayesian linear mixed-effects mode…
Large Language Models for Text Classification
Large language models (LLMs) have tremendous potential for social science research as they are trained on vast amounts of text and can generalize to many tasks. We explore the use of LLMs for supervised text classification, specifically the application to stance detection, which involves detecting attitudes and opinions in texts. We examine the performance of these models across different architectures, training regimes, and task specifications. …
Parental absence during childhood and intergenerational solidarity in adulthood in China
ObjectiveWe aim to examine whether having been separated from parents during childhood influences multiple dimensions of intergenerational solidarity during adulthood.BackgroundIn developing countries, many children experience geographic separation from one or both parents due to parental out-migration. Previous research has examined the concurrent effects of parental migration on parent-child relationships, but little is known about the long-ter…
Large Language Models for Text Classification
Large language models (LLMs) have tremendous potential for social science research as they are trained on vast amounts of text and can generalize to many tasks. We explore the use of LLMs for supervised text classification, specifically the application to stance detection, which involves detecting attitudes and opinions in texts. We examine the performance of these models across different architectures, training regimes, and task specifications. …
Parental absence during childhood and intergenerational solidarity in adulthood in China
ObjectiveWe aim to examine whether having been separated from parents during childhood influences multiple dimensions of intergenerational solidarity during adulthood.BackgroundIn developing countries, many children experience geographic separation from one or both parents due to parental out-migration. Previous research has examined the concurrent effects of parental migration on parent-child relationships, but little is known about the long-ter…
The effects of environmentalism on fertility in the United States
Environmental issues such as climate change have become major contemporary concerns that affect beliefs and, in some cases, behaviors. We examine whether and how environmentalism may have contributed to the second demographic transition that has driven declining fertility in some parts of the world since the 1970s. Data come from the 2006–2014 and 2016–2020 General Social Survey rolling panels in the USA. We fit Bayesian linear mixed-effects mode…
Large Language Models for Text Classification
Large language models (LLMs) have tremendous potential for social science research as they are trained on vast amounts of text and can generalize to many tasks. We explore the use of LLMs for supervised text classification, specifically the application to stance detection, which involves detecting attitudes and opinions in texts. We examine the performance of these models across different architectures, training regimes, and task specifications. …
Family Dynamics and Relationships (2 works) · Psychology (2 works) · Affect (linguistics (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Causality (physics (1 work) · Climate change (1 work) · Closeness (1 work) · Computational and Text Analysis Methods (1 work) · Computer Science (1 work)