The place of the concept of response strength in a natural science of behavior has been the subject of much debate. This article reconsiders the concept of response strength for reasons linked to the foundations of a natural science of behavior. The notion of response strength is implicit in many radical behaviorists’ work. Palmer (2009) makes it explicit by applying the response strength concept to three levels: (1) overt behavior, (2) covert behavior, and (3) latent or potential behavior. We argue that the concept of response strength is superfluous in general, and an explication of the notion of giving causal status to nonobservable events like latent behavior or response strength is harmful to a scientific endeavor. Interpreting EEG recordings as indicators of changes in response strength runs the risk of reducing behavior to underlying mechanisms, regardless of whether such suggestions are accompanied by behavioral observations. Many radical behaviorists understand behavior as a discrete unit, inviting conceptual mistakes reflected in the notion of response strength. A molar view is suggested as an alternative that accounts for the temporally extended nature of behavior and avoids the perils of a response-strength based approach.

We present the mathematical description of feedback functions of variable interval and variable differential reinforcement of low rates as functions of schedule size only. These results were obtained using an R script named Beak, which was built to simulate rates of behavior interacting with simple schedules of reinforcement. Using Beak, we have simulated data that allow an assessment of different reinforcement feedback functions. This was made with unparalleled precision, as simulations provide huge samples of data and, more importantly, simulated behavior is not changed by the reinforcement it produces. Therefore, we can vary response rates systematically. We've compared different reinforcement feedback functions for random interval schedules, using the following criteria: meaning, precision, parsimony, and generality. Our results indicate that the best feedback function for the random interval schedule was published by Baum (1981). We also propose that the model used by Killeen (1975) is a viable feedback function for the random differential reinforcement of low rates schedule. We argue that Beak paves the way for greater understanding of schedules of reinforcement, addressing still open questions about quantitative features of simple schedules. Also, Beak could guide future experiments that use schedules as theoretical and methodological tools.

We pay tribute to Rachlin's work stating that researching and writing for posterity is an act of selfcontrol and altruism. We show how Rachlin's work influenced a series of seminars at the University of São Paulo (Brazil) based on his book from 1989, Judgment, Decision, and Choice. This influence is illustrated through two empirical exercises conducted during our seminars, where students were actively involved in data collection and analysis. The first exercise is about judgment of randomness involving coin tossing. The second is a replication of a procedure by Jones and Rachlin ( 2006) about social discounting of monetary quantities. We use these empirical examples to highlight some of Rachlin's major contributions to the science of behavior and their implications to our seminars and to ourselves as researchers.

É comum, durante a formação de futuros analistas do comportamento, se ensinar que a definição de reforçamento passa exclusivamente pelo aumento da frequência ou taxa de uma única classe de respostas. Com base em dados disponíveis na literatura discute-se a pertinência da versão padrão da teoria do reforço, bem como busca-se uma descrição mais abrangente das seguintes funções: (1) seleção; (2) indução; (3) ordenação e organização; e (4) expansão do repertório comportamental. A frequência, embora seja uma medida conveniente, não compreende a abrangência de uma teoria plausível do reforçamento, que deve compreender sua relação com filogênese, com outras classes de resposta que não aquela à qual o reforçador é contingente, e com as decorrências da aplicação sistemática do reforçamento no repertório comportamental. Uma teoria restrita à medida da frequência já não se sustenta à luz dos dados operantes.