2021
DOI: 10.1002/jeab.671
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Exploring a Training IRAP as a single participant context for analyzing reversed derived relations and persistent rule‐following

Abstract: Rule‐governed behavior and derived stimulus relations have always shared strong conceptual links within behavior analysis. However, experimental analysis linking the two domains remains limited. The current study consisted of three experiments that aimed to continue to bridge this experimental gap. The first experiment sought to establish the extent to which a training version of the implicit relational assessment procedure (IRAP) could be used to establish and successfully reverse experimentally established d… Show more

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Cited by 8 publications
(1 citation statement)
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“…With respect to research on rule-governed behavior, a relatively new research program has manipulated the levels of derivation, coherence, and flexibility of mutually entailed relations, combinatorially entailed relations, and relational networks, and assessed their impact on persistent derived rule-following (e.g., Bern et al, 2021;Bianchi et al, 2021;Harte et al, 2017, Harte, Barnes-Holmes, Moreira et al, 2021, both at the group and single-participant levels. Approaching rule persistence from this perspective has also led to substantive conceptual developments in this area (Harte & Barnes-Holmes, 2021a; Harte, Barnes-Holmes, Barnes-Holmes, & Kissi, 2020).…”
Section: Extending the Hdml To Other Research Areasmentioning
confidence: 99%
“…With respect to research on rule-governed behavior, a relatively new research program has manipulated the levels of derivation, coherence, and flexibility of mutually entailed relations, combinatorially entailed relations, and relational networks, and assessed their impact on persistent derived rule-following (e.g., Bern et al, 2021;Bianchi et al, 2021;Harte et al, 2017, Harte, Barnes-Holmes, Moreira et al, 2021, both at the group and single-participant levels. Approaching rule persistence from this perspective has also led to substantive conceptual developments in this area (Harte & Barnes-Holmes, 2021a; Harte, Barnes-Holmes, Barnes-Holmes, & Kissi, 2020).…”
Section: Extending the Hdml To Other Research Areasmentioning
confidence: 99%