This repository contains materials covering natural language processing analyses both planned and exploratory on paragraphs written by participants on one of six controversial topics. From these analyses, we hope to gain an understanding of differences in political reasoning, namely in humility and openness to political experience.

Growing research is dedicated to uncovering the psychological correlates and causes of politically biased reasoning. Yet, most research has been conducted at the variable-level rather than the person-level of analysis. We addressed this gap in the literature in a large sample of U.S.-based adults (N = 799). We used latent class analysis to identify whether there are groups of individuals who differ in (a) their level of politically biased reasoning (e.g., providing balanced arguments about political topics) and (b) variables that bear on politically biased reasoning (e.g., intellectual humility). We identified three classes: those who are politically engaged and unknowledgeable ( “Zealots”), those who are politically engaged and knowledgeable (“Sages”), and those who are politically apathetic (“Apaths”). Identified Sages also scored the highest on intellectual humility, trust in science, and cognitive reflection, and they scored the lowest on political overconfidence and affective polarization. Altogether, our study illuminates who is most susceptible to politically biased reasoning and points to intriguing future directions on how to intervene on politically biased reasoning.

Preregistrations for all studies are available on the Open Science Framework:

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├── README.md
├── LICENSE
├── Code
│   ├── R
│   └── Python (Jupyter Notebooks)
├── Data
└── Dictionaries