cs.AIAug 31, 2026

Different representation learning objectives recover distinct latent structures from the same psychometric data

Authors: Cong CaoTassos C. KyriakidesPambos Vrasidas

Organizations: Department of Biostatistics, Yale School of Public Health, Yale University, New Haven · Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, USA · Center for the Advancement of Research & Development in Educational Technology (CARDET), Nicosia, Cyprus

Abstract

Psychometric questionnaires contain rich item-level information, yet it remains unclear whether different representation learning objectives recover the same latent organization. We investigated this question using 757 matched teacher-child pairs from the baseline assessment of the Cyprus ProW preschool trial. Behavioral structure was characterized from child SDQ, ASBI, and CBRS item responses using principal component analysis and clustering, yielding four behavioral phenotypes. A contrastive objective substantially improved teacher-child retrieval relative to PCA-based representations, increasing Top-1 accuracy from 0.13% to 7.27% and Top-10 accuracy from 1.98% to 56.14%. However, contrastive representations preserved behavioral phenotype structure less effectively than PCA-based representations. A multi-task objective jointly optimizing alignment and behavioral prediction partially restored behavioral organization but reduced retrieval performance. These findings indicate that teacher-child correspondence and behavioral phenotypes represent distinct forms of latent organization and demonstrate that the latent structure recovered from linked psychometric data depends on the representation learning objective.

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