Methodology

A comprehensive overview of how the Civic Language Perceptions Survey was designed, conducted, and analyzed.

Survey Design

The Civic Language Perceptions Survey employed a comprehensive approach to capture public perceptions of key terms related to democracy, civic engagement, and equity. Participants were asked to rate their familiarity and perceptions of 21 key civic and political terms.

2025 Survey Methods

More in Common US sampled 5,393 registered voters, including an oversample of 695 respondents from Arizona, from November 18th to 26th, 2025 on behalf of Philanthropy for Active Civic Engagement (PACE).

  • Sample Size: 5,393 registered voters
  • Arizona Oversample: 695 respondents
  • Field Dates: November 18-26, 2025
  • Margin of Error: ±1.3%
  • Conducted by: More in Common US
  • Commissioned by: Philanthropy for Active Civic Engagement (PACE)

Weighting

Results are weighted on:

  • Age by gender (interlocked)
  • Race/Ethnicity
  • Education
  • 2024 vote
  • US region

Measures

Three primary measures were collected for each term in the 2025 survey:

  • Positivity: How positively or negatively the term is perceived (Positive, Neutral, Negative, Not Familiar)
  • Ownership: Whether the term feels "meant for me" or "meant for someone else" (5-point scale)
  • Togetherness: Whether the term brings people together or drives them apart (5-point scale from "Brings together a lot" to "Drives apart a lot")

Demographic Variables

Comprehensive demographic data was collected including:

  • Political ideology (Very liberal to Very conservative)
  • Age group
  • Education level
  • Race/Ethnicity
  • Gender
  • Geographic region
  • Urban/Rural status
  • Religion
  • Generation

Research Team

More in Common US: Fred Duong, Paul Oshinski, Amy McIsaac, Trystan Loustau, Emily Gerdin

Published: December 2, 2025

Limitations

As with any survey research, there are limitations to consider:

  • Self-reported data may be subject to social desirability bias
  • Cross-sectional design limits causal inference
  • Some demographic subgroups have smaller sample sizes