Disentangling and Reassembling: Unveiling Hidden Patterns in Gender Attitudinal Surveys

Abstract

This study addresses the complexities of midpoint and non-substantive responses, such as “Don’t Know,” in Likert scale surveys on gender attitudes. While existing research often assumes these responses are neutral or random, this study challenges that notion by applying the item response tree model to disentangle respondents’ attitudes from their response tendencies. Analysis of data from the Chinese General Social Survey shows that traditional gender attitudes are associated with a higher likelihood of such responses, indicating biases in conventional methods. After disentangling these elements, I reassemble them through latent profile analysis to examine the dominant configurations of gender attitudes and response tendencies. Five distinct profiles emerge: Passionate Egalitarians, Genuine Neutrals, Forthright Moderates, Evasive Traditionalists, and Unembellished Traditionalists. Passionate Egalitarians advocate strongly for gender equality, while Evasive Traditionalists use non-substantive responses to conceal traditional views. This study provides a refined approach to rating scale analysis, advancing both sociological methodology and gender studies.