Toward Minimum Sufficient Information for Representing Variable Operationalization in Quantitative Research: A Functional Parsimony Framework

Abstract

Variable operationalization connects scientific attributes and constructs with expressions that can be empirically recorded, yet representations of this transition often combine information serving different methodological functions. This conceptual article develops a functional parsimony framework for evaluating which information functions may constitute a minimally sufficient general-purpose synoptic representation. The framework was developed through function-directed theoretical synthesis, adversarial precedent search, functional decomposition, explicit admission criteria, conceptual ablation, and stress tests across heterogeneous classes of variables. It retains a candidate core of four functions: variable, operational referent, final values, and value structure. The first three represent the selected transition from the variable of interest to its recordable expressions; the fourth characterizes justified relations among those expressions. Candidates for a fifth function were retested, especially data source/provenance and temporal or observation context. Under the proposed admission criteria, neither was retained as an independent fifth function in the adversarial cases examined. When source or context is constitutive, the framework represents it within the variable or operational referent; when it serves traceability, procedural, or design functions, it is documented in the corresponding layers. The proposal therefore distinguishes the synoptic core from conceptual, operational, measurement, provenance, and analytical specification. Functional parsimony means preserving information required by the stated function, avoiding redundancy at the same level, and locating additional information where its function can be adequately documented. Sufficiency of the core is presented as a falsifiable design objective, not as a demonstrated universal property. Practical general-purpose usability remains an empirical hypothesis and requires independent inter-rater and comparative task validation.

The authors' abstract, as published at the source. Measurement Interdisciplinary Research and Perspectives, 2026 · DOI ↗