Institutions such as universities are responsible for a significant amount of recyclable material entering landfills. This problem could be addressed in part by increasing the percentage of waste recycled by consumers on campuses. Building on previous research, we evaluated the effects of bin proximity and visual prompts on rates of recycling within a university building. The total weight of recyclable materials (aluminum, plastic, and paper) placed into the building’s garbage and recycling bins was measured each day, and a reversal design was employed in which the environmental arrangement of the recycling bins was systematically manipulated. Both interventions produced a decrease in the amount of recyclable material being thrown in the trash cans, with visual prompts plus bin proximity being slightly more effective than bin proximity alone. However, neither intervention produced large increases in recycling. Interpretations of these findings and suggestions for future researchers are discussed.

This study proposes the use of an experimental analogue of natural resource exploitation to evaluate the effects of the real-time displaying of the amount of available resources and the provision of written feedback messages on the resource extraction behavior of participants sharing a common-pool whereby participants are physically and verbally isolated from each other. The experiment involved the application of a three-member common-pool resources (CPR) game. The members of the groups sharing the CPR were changed periodically and were allowed to talk briefly to each other so that an experienced participant could give instructions to a newcomer. In this way, it was also possible to evaluate how the accuracy of instructions regarding resource preservation and sustainability affects group member resource extraction patterns and CPR maintenance in the long run. Twenty-two college students took part and were distributed into three groups: Control, Display, and Feedback. The amount of resources extracted individually and by the groups in every round of the game was analyzed, as were the verbal responses of the experienced participants when giving instructions to newcomers. Results showed that the manipulated variables were effective for the short-term decrease in the amount of resources extracted by the members of the Display and Feedback groups. The accuracy of the instructions was also important for the sustained maintenance of the pattern of consumption established by the manipulated variables, leading to the recovery and the preservation of the resources in a greater number of the game’s rounds.

In Selection by Consequences , Skinner (1981) described a causal model that explains human behavior as a joint product of three levels of selection: (i) the contingencies of survival involved in natural selection, (ii) the contingencies of reinforcement involved in the selection of individual behavior, and (iii) contingencies of an evolving social environment. Since then, researchers from behavior analysis and other fields such as biology and anthropology have used an evolutionist/selectionist approach to greatly improve our understanding of those three levels of analysis. As our knowledge of each level has expanded, the borders between them and their belonging to specialized academic domains has become less clear. Even though Skinner (1981, p 502) stated that “each level of variation and selection has its own discipline – the first, biology; the second, psychology; and the third anthropology”, we argue that Selection by Consequences sets a milieu for behavior analysis to take part in the analysis of the integrated relation among all levels of analysis. In this commentary to Skinner’s (1981) paper, we aim to point out some advances in behavior analysis that may contribute to bridging the gap between the three levels of analysis described by Skinner. In doing so, we will briefly describe some relations between natural and behavioral selection and between behavioral and cultural selection. Additionally, we discuss an alternative model to analyze selection of cultures.

As concerns regarding the current and future state of the planet continue to grow, the need to understand the behavioral mechanisms that underlie behaviors linked to large-scale, probabilistic and delayed outcomes become more critical. Delay discounting refers to decline in the subjective value of a stimulus as the delay-interval to access that stimulus increases. In this article, the relevance of delay discounting to issues of sustainability is explored. The research on delay discounting and related processes is summarized, specifically research that relates discounting and sustainability issues. Implications for behavior change and future research are discussed.

Historically, behavior analytic research and practice have been grounded in the single subject examination of behavior change. Within the behavior analytic community, there remains little doubt that the graphing of behavior is a powerful strategy for demonstrating functional control by the independent variable; however, during the past thirty years, various statistical techniques have become a popular alternative form of evidence for demonstrating a treatment effect. Concurrently, a mounting number of behavior analytic investigators are measuring multiple dependent variables when conducting statistical analyses. Without employing strategies that protect the experimentwise error rate, evaluation of multiple dependent variables within a single experiment is likely to inflate the Type I error rate. In fact, with each additional dependent variable examined in univariate fashion, the probability of “incorrectly” identifying statistical significance increases exponentially as a function of chance. Multivariate analysis of variance (MANOVA) and several other statistical techniques can preclude this common error. We provide an overview of the procedural complications arising from methodologies that might inflate the Type I error rate. Additionally, we provide a sample of reviewer comments and suggestions, and an enrichment section focusing on this somewhat contentious issue, as well as a number of statistical and neural network techniques that enhance power and preclude the inflation of Type I error rates

The majority of criminal cases are decided through plea bargaining and probability discounting (i.e., the change in the value of an outcome as it becomes less probable) may aid in the understanding of this process. University students were asked to complete a probability-discounting task involving three legal and two monetary outcomes. Groups were divided in terms of the race of the recipient of the outcome and the participant’s sex. Results showed that the crime of murder was discounted more steeply than the other scenarios, that the predictions of the leading theory of plea bargaining (i.e., decision theory) were inaccurate, and that males and females discounted differently (only) when the recipient was African American (regardless of the type of outcome). The present results have theoretical and practical implications and should serve highlight the utility of studying plea bargaining within a probability-discounting framework.

The authors reviewed human empirical studies from 1987–2010 in the Journal of the Experimental Analysis of Behavior (JEAB), Journal of Applied Behavior Analysis (JABA), Journal of Organizational Behavior Management (JOBM), and Psychological Record (PR). Out of 2286 empirical studies, the authors classified 45 as simulation research, which fell into 4 main categories including organizational, gambling, financial, and other. JOBM contained over half of the simulations, while JEAB contained two. A subsequent citation analysis found that the original simulations informed 15 service-delivery articles, across five journals. In addition, the original articles also informed 35 other behavioral simulations across 19 journals. Simulation research could be ideally placed between theory and application to facilitate empirical research and applications in complex human behavior and the development of an empirically validated, comprehensive, system of behavior analysis.

Despite several decades of effort, the field of psychology has largely failed to make any substantial gains in promoting widespread adoption of environmentally relevant behaviors (ERBs), regulations, or public policies. At the same time, huge impacts can be observed within other domains of science and engineering. The bulk of psychology’s contributions on the topic come from two major schools of thought, social/ environmental psychology and behavior analysis. This paper reviews these contributions in terms of the strengths and weaknesses of each approach both practically and conceptually. Understanding the role of verbal behavior in influencing environmentally significant action is suggested as a means of guiding research efforts toward the discovery of practical solutions. Contemporary behavioral analysis of language is cited as an example of behavior-change technology that suggests pragmatic solutions and promising avenues for future investigation.

Educating the public accurately about Applied Behavior Analysis (ABA) is an important undertaking, not least because misconceptions and myths about ABA abound. In this paper we argue that, unfortunately, the efforts of many dedicated professionals and parents to disseminate accurate information about the benefits of ABA for children diagnosed with autism spectrum disorder (ASD) are damaged by a few behavior analysts whose focus seems to be more on monetary gains than social responsibility. We cite examples of the resulting harm to the public image of behavior analysis from a number of European countries. We conclude by calling upon fellow scientists to unite in their opposition to unscrupulous abuses of free market forces for short-term monetary gains that damage the dissemination of the science of behavior analysis and thereby ultimately disadvantage those who should benefit primarily from our science, i.e., some of the most vulnerable citizens of society.