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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Hierarchical classification as relational framing.

Brian Slattery1, Ian Stewart

  • 1National University of Ireland, Galway.

Journal of the Experimental Analysis of Behavior
|December 7, 2013
PubMed
Summary
This summary is machine-generated.

This study models hierarchical classification using relational framing. Findings demonstrate how contextual cues can establish and derive complex class structures, advancing our understanding of cognitive development.

Keywords:
asymmetrical class containmenthierarchical classificationrelational frame theorytransitive class containmentunilateral property induction

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Area of Science:

  • Cognitive Psychology
  • Developmental Psychology
  • Behavioral Science

Background:

  • Hierarchical classification is a fundamental cognitive ability.
  • Existing models often lack a clear procedural account of its development.
  • Relational Frame Theory offers a potential framework for understanding such complex behaviors.

Purpose of the Study:

  • To model hierarchical classification as contextually controlled, generalized relational responding (relational framing).
  • To experimentally establish and test derived hierarchical relations and transformations of function.
  • To investigate the cognitive processes underlying class containment and property induction.

Main Methods:

  • Experiment 1 utilized nonarbitrarily related multidimensional stimuli to establish contextual cues for 'member of' and 'includes' relations.
  • A network of arbitrary stimuli was trained to establish hierarchical relations, followed by tests for untrained relations and function transformation.
  • Experiment 2 employed "fuzzy category" stimuli and a controlled test for transformation of functions.

Main Results:

  • Relational framing patterns exhibited transitive and asymmetrical class containment.
  • Unilateral property induction was observed, consistent with cognitive developmental theories.
  • The model successfully demonstrated the derivation of untrained hierarchical relations.

Conclusions:

  • Hierarchical classification can be effectively modeled as generalized relational responding.
  • Contextual control plays a crucial role in establishing and deriving hierarchical structures.
  • The findings support Relational Frame Theory's applicability to complex cognitive phenomena like hierarchical classification.