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Deriving Addiction
Published in Hanna Pickard, Serge H. Ahmed, The Routledge Handbook of Philosophy and Science of Addiction, 2019
The equilibrium points in the local bookkeeping panels of Figures 2.1 and 2.2 are identical to experimental psychology’s “matching law” equilibrium points (Herrnstein 1970). This result, as the label “matching law” suggests, has been observed in hundreds of experiments, conducted both in and outside of laboratory settings (Davison and McCarthy 1988). In experiments with infra-human subjects, matching is the expected result, despite reliably producing substantially suboptimal returns under some conditions (e.g., those shown in Figure 2.1). However, in a choice experiment with pigeons in which the experimenters introduced stimuli that explicitly signaled global bookkeeping reward bundles, the pigeons deviated from matching as predicted by global bookkeeping thereby increasing reward rate (Heyman and Tanz 1995)—a result that underscores the cognitive dimensions of local and global bookkeeping.
Theories and Models of Health Behavior Change
Published in Deborah Fish Ragin, Health Psychology, 2017
The EVT’s inability to account for more than one factor that also influences behavior is a limitation of the theory. To address this limitation, Herrnstein (1970) and later Borders (2004) proposed adding the concept of matching law to EVT. The matching law states that decisions to engage in a specific behavior are influenced, in part, by reinforcements for the intended behavior as well as reinforcements for alternate behaviors (Herrnstein, 1961). If the reinforcement for an alternate behavior is greater than the reinforcement for the intended behavior, then the likelihood is greater that an individual will perform the alternate behavior.
Advances in AAC intervention: some contributions related to applied behavior analysis
Published in Augmentative and Alternative Communication, 2021
Joe Reichle, Robert E. O’Neill, Susan S. Johnston
The matching law (Herrnstein, 1961) was formulated to describe how individuals might allocate their behavior in different ways depending on the schedules and quality of reinforcement available for different behaviors. For example, suppose that, based on experience, a student had learned that requesting a snack from one teacher resulted in a desired item approximately 70% of the time, while similar requests directed toward another teacher resulted in desired items approximately 30% of the time. Research on the matching law has demonstrated that individuals will respond to the two options at a rate that is proportional to the reinforcement obtained from each (Cooper et al., 2020). Therefore we would expect the student to direct requests to the first teacher approximately 70% of the time, with remaining requests directed to the second teacher. Such behavior allocation may also be influenced by the quality and magnitude of reinforcement (Cooper et al., 2020). For example if both teachers responded equally often to requests, but one offered more highly preferred snack items, we would expect to see more requests directed that teacher’s way. Such influences are important to consider, especially in situations where attempts are being made to teach appropriate desired behaviors as alternatives to challenging behavior (e.g., aggression, self-injurious behavior, etc.). Response efficiency refers to these and other applications related to the matching law and other factors that may influence the likelihood of performance of certain behaviors versus others. Along with rate and quality of reinforcement, factors such as immediacy of reinforcement and physical effort needed to perform a response may come into play. These concepts, along with examples, are discussed in the sections that follow.
Opening the Educational Leadership Door: Promoting the Collaboration of OBM and Education
Published in Journal of Organizational Behavior Management, 2021
Natalie R. Starling, Carly Vissicchio, Katharine Grottke
Beyond the use of a specific tool like the PDC-HS, a broader understanding and dissemination of behavior principles and processes in educational settings could be beneficial. Strategies for addressing maintaining variables for employee behavior and supporting lasting change could be found through educator understanding of multiple concepts, including (to name a few): the influence of reinforcement allocation under the concepts and processes found in the Matching Law (Daniels & Daniels, 2007; Redmon & Lockwood, 1986; Sigurdsson & Austin, 2006), the use of pinpointing, and why pinpointing a few behaviors that are likely to have the greatest impact on desired outcomes is effective (Braksick, 2007), and the influence of naturally occurring contingencies (Scherrer & Wilder, 2008) among many other variables worthy of examination. Putnam and Kincaid (2015) highlighted the opportunity for behavior analysis in terms of supporting the expansion of PBIS into educational settings, and we hypothesize that OBM, specifically, could provide educational settings with the opportunity for increased sustainability of system-wide initiatives like PBIS through many of the aforementioned concepts and strategies. These strategies include pinpointing leadership and employee behaviors most closely linked with the critical components of PBIS, identifying and maintaining variables for employee behaviors which are integral to PBIS implementation, as well as applications of behavior science concepts (e.g., Matching Law) to encourage and support changes in employee behavior to adopt new practices. Since the early 1960s, R.J. Hernstein’s research on the Matching Law showed that behavior matches reinforcement (Hernstein, 1961; Reed & Kaplan, 2011). An understanding of the principles of the Matching Law could, as one example, help school leaders and other staff interpret educators’ allocation of efforts to particular tasks. For instance, a perspective which includes an understanding of the Matching Law may reveal that new tasks related to initiatives like PBIS may not be strongly associated with employee access to reinforcement (e.g., supervisor praise/appreciation) or punishment (e.g., supervisor reprimand), or this association may not be as powerful as previously established contingencies related to continued adherence to other instructional or classroom behavior management practices.