1189 - HOW DOES THE STRUCTURAL EQUATION MODELING ADDRESS THE ROLE OF PERSONAL VALUES IN SHAPING POLITICAL TRUST AND PERCEIVED DISCRIMINATION?

Session: P_D11S001 - Poster Session 1 - Division 11
AUTHORS:
Dindar Nefide (Middle East Technical University Department of Business Administration ~ Ankara ~ Turkey) , Saraç Melike (Hacettepe University Institute of Population Studies ~ Ankara ~ Turkey)
Abstract text:
Discrimination is a major social problem undermining individuals' well-being. This study examines how personal values influence political trust and, in turn, perceptions of discrimination. It focuses on three values of Schwartz's value framework: conformity, tradition, and security. Prior research has mainly investigated political trust as a consequence of discrimination. However, the current study presents a different perspective through examination of political trust as a possible antecedent of perceived discrimination. While most previous studies have concentrated on people's perceptions of their experiences of discrimination, this study addresses whether they define themselves as members of a group that has been discriminated against. Although some of the relationships between the constructs have been analyzed separately by previous research, analyzing them as a whole complex model by structural equation modeling (SEM), an appropriate way to analyze relationships between social constructs, is an important methodological contribution.


Data were derived from the European Social Survey Round 11, conducted in the United Kingdom in 2023 with a sample of 1684 individuals aged 15 and over. SEM was used to test the mediation model linking individual values, political trust, and perceived discrimination. These concepts can be evaluated as difficult to measure, and it is worth investigating the factors affecting them.


Findings show that conformity, tradition, and security positively affect political trust. Political trust also positively affects conformity, tradition, and security and negatively affects perceived discrimination. Using cross-sectional data from a single country may limit causality and cross-cultural generalizability. Self-administered questionnaires may have led to social desirability bias that could affect the survey responses. Observable variables were measured by one or two items, which may introduce measurement error. Despite these limitations, results provide important insights for policymakers to build trust by considering different personal values for the safety and well-being of people from different demographic groups.