Logo of the Physikalisch-Technische Bundesanstalt

A Theory of Psychological Measurement Based on Relational Responding

Kolloquium der Abteilung 9

We present a theory-based approach to psychological measurement based on the idea that psychological attributes are emergent properties of relational responding. Empirical findings suggest that relational responding is operant behavior and, as such, selected by its environmental consequences. Following the formal requirements of representational measurement, we propose that a measurable psychological attribute emerges, if and only if relational responses are selected such that the resulting structure (i.e., the grammar of responding) is isomorphic to a subset of the real numbers. Given such an isomorphism, psychological attributes can be measured either directly by observation of the relational response structure, or indirectly by means of a consistent set-mapping between the objects of the relational response structure and a corresponding numerical structure (e.g., a rating scale).

We further embed the concept of emergent psychological attributes in the theory of operant selection, where selection is understood as a multilevel process that shapes behavior with regard to its expected fitness consequences. Since fitness is itself a quantitative attribute, we hypothesize that quantitative psychological attributes emerge if and only if the environmental contingencies allow for a reliable prediction of expected amount of fitness gain. Consequently, measurable psychological attributes are context-dependent fitness predictors that may function as discriminative stimuli for expected fitness gains given a certain action is taken in that context.

The theory clarifies what psychological attributes are, why they are sometimes quantitative and sometimes not, how they can be measured and why we should expect quantity in the realm of psychology in the first place. Moreover, the theory is empirically rich, yielding several unique hypotheses that can be tested experimentally.

Teilnahme per Stream: www.conf.dfn.de/stream/nr5hfuu882ngd

Teilnahme per VK: conf.dfn.de/webapp/

Gast-Pin: 9090