A Deterministic Framework for Transforming Multi-Informant Observational Data into Structured Descriptors: A...

Multi-informant observational data obtained from parents and educators provide rich but context-dependent information. However, these data are rarely transformed into structured representations that can be consistently shared and interpreted across contexts without relying on diagnostic classification.

This study aimed to propose and implement a deterministic framework for transforming multi-informant observational data into structured, interpretable descriptor sets, and to examine its feasibility under controlled conditions. The framework targets an intermediate representation layer for structuring observational data prior to interpretation or decision-making.

Parent- and educator-reported questionnaire data were used as standardized inputs to a predefined deterministic framework. Child-centered signals were derived from parent reports, while educator reports were incorporated as educator-derived contextual signals. The framework applies a transparent rule-based mapping process to generate context-preserving sets of predefined structured descriptors without reliance on machine learning or statistical modeling. Structural behavior was examined using controlled simulated input conditions.

The framework consistently generated a limited and prioritized set of descriptors for each input profile. Outputs were structurally stable and reproducible across all predefined input configurations, demonstrating consistent transformation of multi-informant data into structured representations.

This study demonstrates the feasibility of a deterministic framework for organizing multi-informant observational data into structured, non-diagnostic descriptors. By introducing a reproducible intermediate organizational layer, the framework provides a transparent approach to cross-context information structuring that may be applicable to other multi-context observational settings involving multi-informant data integration.