Experimental Data on Motivated Reasoning and Trust in News

The dataset from Princeton University researcher Michael Thaler supports a study on motivated reasoning in belief formation. It contains experimental data analyzing how subjects assess the veracity of information sources that contradict their preconceived beliefs. Evidence covers topics including immigration, income mobility, crime, racial discrimination, gender, climate change, and gun laws.

Use Cases

• Modeling belief updating patterns based on experimental subject responses.
• Analyzing politically-motivated reasoning across topics like immigration and climate change mentioned in the description.
• Identifying factors that evoke motivated beliefs versus Bayesian updating as described in the experimental design.

Strengths

• Data is linked to a peer-reviewed experimental design from a researcher at Princeton University.
• Evidence covers multiple high-salience political and social topics as listed in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• License is listed as closed, restricting reuse and distribution.

Provenance

Source

Michael Thaler, Princeton University

Collection Method

Novel experimental design to identify motivated reasoning from Bayesian updating.