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Description: This study is the first to investigate subject-level variability in sociolinguistic evaluative judgements by 30 adult L2 German learners and explore whether the observed variability is characterizable as a function of individual differences in proficiency, exposure, and motivation. Since group-level estimates did not paint an accurate picture of the individual, we propose methods capable of integrating population-level estimates with person-/ensemble-centered approaches so as to reconcile generalizability and individuality. Using random effects from Bayesian mixed-effects models, we found that global subject-level variability in evaluative judgements was not predicted by individual differences. By building homogeneous ensembles (= subgroups of individuals with similar evaluative judgements), however, it was possible to assess whether ensembles were characteristic of certain levels of individual differences. This ensemble-centered approach presents an innovate way to address the group-to-individual generalizability issue in cross-sectional data and transcend individual variety in order to make tentative generalizations of individual cases to wider populations.