# Research Overview

*Understanding life course inequality through trajectories, timing, and social institutions*

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## Overview

My research examines how life course risks—such as divorce, unemployment, or social exclusion—intersect with institutional structures and social stratification to produce long-term inequality. I analyze how social institutions and welfare regimes shape the timing, duration, and sequences of key life events, and how these pathways create or mitigate disparities across and within social groups.

I use panel data and advanced statistical and machine learning tools—such as causal inference, sequence analysis, and deep learning—to capture these dynamics and simulate counterfactual life trajectories.

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## Core Research Themes

### 🔹 1. Social Stratification Perspective

**Question**: How do welfare states and mobility regimes shape the distribution of life risks and opportunities?

**Focus**: National contexts, class structures, institutional inequality

### 🔹 2. Life Course Perspective

**Question**: How do timing, duration, and sequences of life events create cumulative disadvantage?

**Focus**: Trajectory-based causal inference, post-divorce transitions, sequence modeling

### 🔹 3. Infracategorical (Within-Group) Inequality

**Question**: How do divergent experiences and resources within a group (e.g., among women, or within racial categories) shape stratification?

**Focus**: Skin color, gender ideology, intersectionality across the life course

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## Methods and Data

I use:

- Longitudinal panel data (e.g., NLSY79, Korean data, synthetic simulations)

- Machine learning and deep learning (e.g., Transformer-based g-computation)

- Causal inference (e.g., g-formula, Super Learner, plausibility filtering)

- Sequence analysis and trajectory clustering

These tools allow me to model long-term dynamics and test realistic, interpretable counterfactuals.

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## Vision

The ultimate goal of my research is to inform civic and policy decisions by understanding how structural risks unfold over time. I aim to develop models that not only estimate causal effects, but explain when and for whom life risks accumulate—so that targeted, meaningful interventions can be designed to support equity across the life course.

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📘 Curious about how I came to this work?

👉 [Read My Research Story →](#)

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## Selected Publications

- Quadlin, N., Jeon, N., Doan, L., & Powell, B. (2022). *Untangling perceptions of atypical parents*. *Journal of Marriage and Family*.

- Lundberg, I., Brand, J. E., & Jeon, N. (2022). *Researcher reasoning meets computational capacity: Machine learning for social science*. *Social Science Research*.

- Jeon, N. (2023). *Swapping gender traditionalism: Christianity, Buddhism, and gender ideology in South Korea*. *Journal for the Scientific Study of Religion*.