Pixel International Conferences

School dropout and educational disengagement are increasingly conceptualized as cumulative and relational processes shaped by the interplay of institutional, familial, relational, and structural factors, requiring multidimensional approaches that account for both the configurations of risk and their social patterning. This study aimed to identify latent profiles of school trajectory risk among Brazilian public school students and to examine how these profiles are sociodemographically patterned across gender, race/ethnicity, socioeconomic status, and student labor participation. Accordingly, a sample of 10,000 synthetic data was used, based on valid responses/answers from students of four Brazilian states (Rondônia, Minas Gerais, Mato Grosso, and Maranhão) who completed the Relational Factors for the Risk of School Dropout Scale – Alternative version (IAFREE-A).The synthetic data was calculated using the Gaussian Copula technique, which considers the association between the observed variables in the dataset to estimate new responses, generating a new and bigger dataset. This approach was considered due to the General Law of Data Protection (LGPD) and the need to ensure the protection of participating children and adolescents. Latent Profile Analysis (LPA) was conducted using the five aggregated dimensions of the IAFREE-A — student–student, student–school, student–school-professionals, student–family, and student–community. Model [1] selection followed an analytic hierarchy process based on multiple fit indices (Akogul & Erisoglu, 2017). The best-fitting solution was a three-class model (BIC = 59,332; entropy = 0.79; minimum classification probability = 0.88), with profiles interpreted as low (27.2%), medium (53.9%), and high risk (18.9%), showing monotonic separation across all five dimensions, with high-risk students presenting elevated scores in the student–school (M = 2.98) and student–community (M = 2.91) domains. Subsequently, chi-square analyses examined associations between profile membership and sociodemographic variables. A statistically significant association emerged for gender (χ² = 118.47; p < .001; V = 0.077): female students were over-represented in the high-risk profile (adjusted residual = +8.91), whereas male students concentrated in the low-risk profile (+8.02). Associations with socioeconomic level (V = 0.033), student employment (V = 0.022), and race/ethnicity (V = 0.007) were weak and non-significant. Findings indicate clear, well-separated multidimensional profiles of school trajectory risk and a robust gendered patterning of vulnerability, supporting a process-oriented understanding of school trajectory risk under LGPD-compliant research conditions.