Left and Right Mean Different Things: How Ideology Labels Vary Across Respondents

Why Interpretations of “Left” and “Right” Matter

Political scientists commonly rely on a single left–right scale to measure ideology, but the labels “left” and “right” are abstract and may evoke different meanings for different people. Paul C. Bauer, Pablo Barberá, Kathrin Ackermann, and Aaron Venetz ask whether these varying associations threaten the comparability of left–right self-placement and could introduce bias into empirical studies of ideology.

How the Study Worked

The authors analyze a unique survey that asked respondents open-ended questions about what the terms “left” and “right” mean to them. They convert those free-text answers into interpretable categories using automated topic-modeling techniques to identify common themes and associations across respondents.

What the Authors Found

• Respondents attach a wide range of associations to “left” and “right” rather than a single, uniform meaning.
• Variation in those associations is systematically linked to respondents’ own left–right self-placement: people on different parts of the scale tend to emphasize different themes when describing the labels.
• Other respondent characteristics such as education and cultural background (notably East vs. West Germany) also correlate with distinct meanings attached to the labels.

What This Implies for Measurement

These patterns imply that the left–right scale is not perfectly comparable across individuals: the same numeric self-placement can reflect different underlying conceptions of politics depending on who is answering. That threatens straightforward interpretation of single-item ideology measures and suggests a source of measurement bias in cross-group comparisons.

Next Steps for Survey Research

Bauer, Barberá, Ackermann, and Venetz argue for more systematic investigation into how respondents interpret abstract political terms used in surveys. Their findings point to the value of validating core survey items (through open-ended probing, multi-item scales, or cross-cultural testing) before using them to draw substantive conclusions about ideological distributions and their correlates.