A stimulus that gains its reinforcing properties through association with a primary reinforcer is termed a secondary or learned reinforcer. This type of stimulus was initially neutral but acquired the ability to increase the frequency of a behavior because of its link to a biologically significant event. For instance, money, originally without inherent value, becomes a powerful motivator because it can be exchanged for food, shelter, or other necessities.
The significance of these learned motivators lies in their practicality and efficiency in shaping behavior. Unlike primary reinforcers, which are often limited by satiation or availability, these secondary stimuli can be used across a wider range of situations and can bridge the gap between a behavior and a delayed primary reward. Historically, the understanding of how these learned incentives operate has greatly enhanced methods of training animals, managing employee performance, and treating behavioral issues in humans.
The following sections will delve deeper into specific examples of how these learned motivators function in different contexts, the neural mechanisms underlying their effectiveness, and how they can be strategically applied to promote desired behaviors.
1. Association with primary reinforcer
The defining characteristic of a learned incentive is its link to a primary, or unconditioned, reinforcer. This association is the mechanism by which an initially neutral stimulus acquires its motivating properties. Without consistent pairing with a primary reinforcer, such as food, water, or relief from pain, the neutral stimulus will not gain the capacity to influence behavior. The establishment of this associative relationship is not arbitrary; it relies on principles of classical conditioning, where the neutral stimulus becomes a predictor of the primary reinforcer.
Consider the use of tokens in a therapeutic setting. These tokens, initially valueless, become powerful tools for behavior modification when consistently exchanged for privileges or desired items (primary reinforcers). The strength of the learned incentive is directly proportional to the strength and consistency of its association with the primary reinforcer. If the link between tokens and the desired items is weakened or severed, the effectiveness of the tokens diminishes accordingly. This dynamic underscores the critical and causal relationship between the association and the maintenance of the learned incentive’s reinforcing properties.
In summary, the enduring power of a learned motivator hinges on the integrity and consistency of its predictive relationship with a primary reinforcer. Understanding this association is crucial for effectively designing and implementing behavioral interventions. Challenges arise when the link is not consistently maintained or when the primary reinforcer loses its inherent value. These factors must be carefully considered to ensure the sustained effectiveness of the learned incentive.
2. Initially neutral stimulus
The genesis of a learned motivator resides in its origin as an initially neutral stimulus. This element is foundational to the definition because it highlights that these incentives do not possess inherent reinforcing qualities. Rather, their capacity to influence behavior is acquired through learning and association. The neutral nature of the stimulus at the outset is a critical distinction, differentiating it from primary reinforcers, which are intrinsically rewarding. For example, a simple sound, such as a click, holds no inherent value. However, when consistently paired with the delivery of food to an animal, the click transforms into a powerful learned motivator capable of shaping complex behaviors. The effectiveness of the clicker stems entirely from its learned association, emphasizing the stimulus’s initial neutrality.
The importance of understanding the initial neutrality lies in the practical implications for designing effective behavioral interventions. Manipulating stimuli to serve as effective learned incentives requires careful consideration of the learning history and consistent pairing procedures. If a stimulus is not initially neutral if it already elicits a pre-existing response the conditioning process may be complicated or ineffective. Furthermore, recognizing the role of initial neutrality prompts researchers and practitioners to focus on the establishment and maintenance of strong associative links. Interventions that fail to account for this fundamental element may yield unpredictable or unsustainable results. For example, using praise as a learned motivator is effective only if the individual being praised perceives the praise as genuine and consistently associates it with positive outcomes or rewards.
In conclusion, the concept of an “initially neutral stimulus” is not merely a theoretical abstraction but a practical consideration that underpins the efficacy of learned motivators. Understanding this initial state and its subsequent transformation into a potent behavioral influence allows for the creation of targeted and successful interventions. Recognizing the role of learning history and associative processes ensures that chosen stimuli can be effectively conditioned and maintained, thereby promoting desired behavioral changes. The challenge remains in systematically and ethically applying these principles across diverse contexts, from animal training to human behavior modification.
3. Learned motivational properties
The acquisition of motivational properties through learning is central to the definition of a secondary reinforcer. An initially neutral stimulus transforms into an effective motivator by virtue of its consistent association with a primary reinforcer. This transformation is not inherent to the stimulus itself but is rather a consequence of the learning process. The degree to which a stimulus becomes motivational depends on several factors, including the consistency and predictability of its pairing with the primary reinforcer, the timing of the pairing, and the individual’s prior learning history. Real-world examples of this phenomenon include the use of grades in education. Grades, originally arbitrary symbols, become powerful motivators because they are linked to privileges, opportunities, and social approval, all of which can act as primary reinforcers. The understanding of these acquired motivational properties is paramount because it allows for the systematic manipulation of environmental stimuli to promote desired behaviors. Without understanding the cause-and-effect relationship by which stimuli acquire motivational influence, behavioral interventions would lack a clear and predictable basis for their application.
A practical application of understanding these acquired motivational properties is in the design of effective token economy systems. In these systems, individuals earn tokens for engaging in target behaviors, and these tokens can later be exchanged for desired goods or privileges. The success of such a system hinges on the token’s ability to act as a learned motivator. If the tokens are not consistently and predictably exchangeable for valuable items or privileges, they will fail to sustain the desired behaviors. Furthermore, the practical significance of this understanding extends to the realm of addiction. Cues associated with drug use, such as specific locations or social contexts, can become powerful learned motivators that trigger craving and relapse. Addressing these learned motivational properties is a crucial component of effective addiction treatment.
In summary, the concept of learned motivational properties is an essential element within the broader definition of secondary reinforcers. It highlights the fact that stimuli do not possess inherent motivational power but acquire it through learning. A thorough understanding of this process is crucial for designing effective behavioral interventions across diverse settings, from education to addiction treatment. While the principles governing the acquisition of motivational properties are well-established, challenges remain in tailoring interventions to individual needs and circumstances and in addressing the complex interplay between learned and intrinsic motivation. Continued research and application of these principles hold the potential for significant improvements in behavior change strategies.
4. Bridge delayed reinforcement
A critical function of a conditioned reinforcer is its capacity to bridge the temporal gap between a behavior and a primary reinforcer. Primary reinforcers, such as food or water, often cannot be delivered immediately following a desired behavior, especially in complex learning scenarios. The delay can significantly weaken the reinforcing effect, hindering the learning process. This is where the learned or secondary reinforcer plays a crucial role. Because the conditioned reinforcer can be presented immediately after the behavior, it serves as a signal that the primary reinforcer is forthcoming. This immediate feedback strengthens the association between the behavior and the ultimate reward, facilitating more effective learning. For example, in animal training, a clicker sound, as a learned reinforcer, can be delivered instantly when an animal performs the desired action, even if food, the primary reinforcer, is delivered seconds later. The clicker bridges that gap, solidifying the behavior. This bridging function is not merely incidental; it is a defining characteristic that enhances the effectiveness of secondary reinforcement, allowing for the shaping of more intricate and delayed behavioral responses.
The practical significance of bridging delayed reinforcement is evident in various human contexts. Consider educational settings where students receive grades or praise for their academic performance. These forms of feedback are conditioned reinforcers that signal the achievement of learning objectives and the potential for future rewards, such as career opportunities. These reinforcers bridge the delay between studying and long-term career success, motivating students to persist in their efforts. Similarly, in workplace settings, performance bonuses or recognition serve as learned motivators that bridge the gap between daily tasks and eventual financial or professional advancement. These incentives maintain employee engagement and productivity by providing immediate feedback on performance and creating a clear path to achieving delayed, but valued, primary reinforcers, like financial security. If the secondary reinforcer does not reliably predict the future availability of the primary reinforcer, its capacity to sustain behavior diminishes, demonstrating the inherent connection between the conditioned stimulus and its associated reward.
In summary, the ability to bridge delayed reinforcement is a fundamental characteristic that distinguishes a secondary reinforcer and underscores its importance in shaping complex behaviors. By providing immediate feedback and signaling the availability of future rewards, conditioned reinforcers enhance learning and motivation across diverse settings. However, challenges exist in maintaining the effectiveness of these reinforcers over time and ensuring that they consistently predict the availability of primary reinforcers. Furthermore, ethical considerations arise when using secondary reinforcers to manipulate behavior, particularly in vulnerable populations. Continued research is needed to refine the application of these principles and address these ongoing challenges.
5. Wider application context
The utility of learned incentives extends far beyond controlled laboratory settings. The significance of a “wider application context” in relation to the definition lies in demonstrating its pervasive influence on behavior across diverse domains of human and animal activity. The defining characteristics of a learned motivator, such as its association with a primary reinforcer, its initial neutrality, and its ability to bridge delayed reinforcement, are not limited to specific environments. Rather, these principles operate in homes, schools, workplaces, therapeutic settings, and even within complex social structures. The capacity to shape behavior through conditioned reinforcement is a fundamental aspect of how individuals learn and adapt to their surroundings. Its reach is substantial, influencing everyday behaviors as well as intricate societal norms.
Examples of this wider context are readily apparent. In education, grades function as conditioned reinforcers, motivating students to study and achieve academic goals. These grades acquire their reinforcing properties because they are associated with parental approval, college admissions, and future career opportunities. Similarly, in the workplace, money serves as a conditioned reinforcer, driving employees to work diligently. While money itself is not intrinsically valuable, it can be exchanged for goods and services that satisfy basic needs and desires. These examples demonstrate how learned incentives shape behavior on a societal scale. Therapeutic interventions, such as token economies, also demonstrate the effectiveness of learned incentives in modifying behavior. In these systems, individuals earn tokens for exhibiting desired behaviors, and these tokens can then be exchanged for rewards. The broader context encompasses parenting techniques, where praise, attention, and privileges serve as conditioned reinforcers that shape a child’s behavior. Understanding this pervasiveness is not merely an academic exercise; it offers invaluable insights into how behavior is influenced and how more effective interventions can be designed. When the wider context is overlooked, interventions may fail to account for the complex web of influences that shape behavior in natural settings.
In summary, the wide applicability of conditioned reinforcement principles is a critical component. Its effectiveness is not limited to controlled research settings. The ability to design interventions based on these principles contributes to behavioral modification and social influence. Recognizing the challenges in implementing these principles across varied settings and ensuring their ethical application is essential. Continued study and implementation of these principles will refine practices.
6. Susceptible to Extinction
The characteristic of being “susceptible to extinction” is intrinsically linked to the very nature of learned incentives, a central element within the domain of behavior analysis. This susceptibility highlights a crucial consideration in the effective use of these acquired motivators. Once the consistent association between the learned incentive and the primary reinforcer is disrupted, the incentive’s capacity to influence behavior diminishes and may eventually disappear.
-
Disruption of Association
The core reason these stimuli are susceptible to extinction lies in the dependence on the link with a primary reinforcer. When this connection is broken, the learned motivator ceases to predict the arrival of the primary reward. For instance, if a token economy system in a classroom is discontinued without a transition plan, where earned tokens are no longer exchangeable for privileges or desired items, the tokens quickly lose their motivational value. The previously reinforced behaviors consequently decrease in frequency, illustrating extinction.
-
Spontaneous Recovery and Reinstatement
Despite the process of extinction, the association is not completely erased. Spontaneous recovery, where the behavior reappears after a period of extinction, can occur. Similarly, reinstatement, where the behavior returns when the primary reinforcer is presented again, demonstrates the latent association remains. This indicates that even after the learned incentive appears to have lost its value, the underlying association can be reactivated, requiring consistent maintenance to prevent the return of previously extinguished behaviors.
-
Contextual Influences on Extinction
The rate of extinction is not uniform and is influenced by context. The environment in which the learned incentive was initially conditioned and subsequently extinguished plays a significant role. For example, if a child is praised (the learned incentive) for completing homework in one environment (e.g., at home) but not in another (e.g., at school), the effect of extinction may be more pronounced in the latter context. The lack of consistent reinforcement across different environments can accelerate the decay of the learned association.
-
Implications for Behavioral Interventions
The inherent susceptibility to extinction requires careful planning and implementation in behavioral interventions. It is important to systematically fade the learned incentive while simultaneously introducing new, more natural reinforcers to maintain the desired behavior. Failure to do so may result in the behavior reverting to its pre-intervention state once the program is terminated. This emphasizes the need for long-term strategies to sustain behavior change beyond the initial intervention period.
In summary, the vulnerability of learned incentives to extinction underscores the importance of continuous reinforcement, strategic fading techniques, and contextual considerations when designing and implementing behavioral interventions. The efficacy of these interventions is dependent not only on establishing the initial association between a stimulus and a primary reinforcer, but also on maintaining and transitioning that association to prevent the unwanted return of extinguished behaviors.
7. Cognitive interpretations involved
The effectiveness of learned incentives is not solely determined by the objective pairing of stimuli but is also significantly influenced by an organism’s cognitive processing of these associations. These interpretations mediate the impact of learned incentives on behavior, adding a layer of complexity to their function.
-
Expectancy and Prediction
A core element involves the organism’s expectation that a learned incentive will lead to a primary reinforcer. The strength of this expectancy, shaped by previous experiences, determines the incentive’s motivational power. For example, if an employee consistently receives a bonus after achieving a specific performance target, a strong expectancy develops that meeting the target will result in the bonus. This expectancy, a cognitive construct, amplifies the bonus’s effectiveness as a learned motivator. However, if there are inconsistent payouts despite achieving the target, this expectancy weakens, diminishing the bonus’s motivational impact. This demonstrates the role of prediction and learned expectations in shaping behavior related to learned incentives.
-
Attribution and Perceived Control
Attributions, or explanations for why an outcome occurred, also affect the efficacy of learned incentives. If an individual attributes the receipt of a reward to their own efforts and abilities, the reward is more likely to reinforce future behavior. This attribution fosters a sense of control, which further enhances motivation. Conversely, if the individual attributes the reward to external factors, such as luck or the actions of others, the reinforcing effect may be weaker. In a classroom setting, students who attribute their good grades to their hard work and understanding of the material are more likely to continue engaging in effective study habits than those who attribute their grades to an easy test. This interplay between attribution and perceived control highlights the cognitive factors that modulate the influence of learned incentives.
-
Evaluative Judgments
The subjective value assigned to both the learned incentive and the primary reinforcer influences their effectiveness. Individuals evaluate the desirability of the reward, taking into account their current needs and preferences. A monetary bonus, for instance, may be highly motivating for someone facing financial hardship, but less so for someone who is financially secure. Similarly, the perceived fairness and equity of the reward system impact its motivational power. If individuals believe that rewards are distributed unfairly, they may become demotivated, regardless of the objective value of the incentive. This subjective evaluation underscores the role of cognitive judgments in moderating the effects of learned incentives.
-
Awareness and Contingency Detection
The extent to which individuals are aware of the relationship between their behavior, the learned incentive, and the primary reinforcer also plays a role. If an individual is unaware of the contingency between their actions and the receipt of a reward, the incentive is less likely to shape their behavior. Conversely, clear and explicit communication of the contingencies can enhance the incentive’s effectiveness. For example, in a workplace training program, clearly outlining the specific behaviors that will be rewarded and the nature of the rewards can increase employees’ motivation to engage in those behaviors. This highlights the importance of awareness and contingency detection in shaping the influence of learned incentives.
These cognitive interpretations underscore that the impact of learned incentives is not a simple, reflexive process. Instead, individuals actively interpret and evaluate these associations, influencing their motivational power. Recognizing the role of cognition provides a deeper understanding and informs design practices of behavioral interventions.
8. Variability in effectiveness
The consistency with which a learned stimulus influences behavior is not uniform. The following outline illustrates factors contributing to this phenomenon.
-
Individual Learning History
The past experiences of an individual exert a profound influence on the effectiveness of a learned motivator. A stimulus that acts as a potent reinforcer for one person might be ineffective or even aversive to another due to differences in their learning history. For example, praise from a supervisor might be highly valued by an employee who has consistently associated such praise with positive outcomes, such as promotions or increased responsibilities. However, an employee with a history of insincere or manipulative praise might view the same stimulus with skepticism, rendering it less effective. The pre-existing associations and beliefs significantly alter how a learned motivator is interpreted and its impact on subsequent behavior. Variability in these factors alters the stimulus’ effectiveness.
-
Contextual Factors
The environment in which the learned motivator is presented can significantly influence its efficacy. A stimulus that is highly effective in one setting might have a diminished effect in another. Consider money, a common example of a learned incentive. While money can be a powerful motivator in a workplace or marketplace setting, its value might decrease in situations where essential goods or services are unavailable, such as in a disaster zone or during a period of extreme scarcity. The relative importance of the learned incentive is subject to fluctuation, depending on the needs of the individual and environmental characteristics. Therefore, contextual considerations are essential when implementing interventions using secondary motivators.
-
Satiation and Deprivation
The principles of satiation and deprivation, typically associated with primary reinforcers, also affect the effectiveness of secondary reinforcers. If an individual is satiated with the resources that a learned motivator can provide, its reinforcing value decreases. Conversely, when an individual is deprived of those resources, the motivator’s effectiveness is amplified. For example, if a student has already attained high grades in all subjects, the offer of extra credit might have little motivational impact. However, if a student is struggling academically and at risk of failing, the same extra credit offer can be a powerful incentive. These fluctuating conditions alter effectiveness.
-
Contingency and Reliability
The reliability with which a learned motivator predicts the arrival of a primary reinforcer is a key determinant of its strength. If the association between the learned incentive and the primary reward is inconsistent or unreliable, the motivator’s effectiveness will diminish. Consider a loyalty program where customers are promised rewards for accumulating points. If the rewards are frequently unavailable, difficult to redeem, or perceived as not worth the effort, customers are less likely to engage with the program. A reliable contingency is crucial for the learned stimulus to maintain its reinforcing properties. If the contingency is weakened, the motivational effects of the learned stimulus are subsequently reduced.
Variability in the effectiveness of conditioned reinforcers highlights the intricate interplay between individual differences, environmental context, and the reliability of predictive relationships. A thorough understanding of these factors is essential for designing successful interventions that leverage the principles of learned motivation. These learned motivation interventions often require ongoing adjustments based on observed behavioral outcomes, a feedback process that is essential.
9. Shaping complex behavior
The shaping of complex behavior is inextricably linked to the principles that define learned incentives. The successive approximation of desired actions, a hallmark of shaping, relies heavily on immediate and consistent feedback. Primary reinforcers, while fundamental, often cannot be delivered with the required immediacy and frequency necessary for effective shaping. Learned incentives, therefore, bridge this temporal and logistical gap. These stimuli, through their association with primary reinforcers, acquire the capacity to provide immediate feedback, guiding an organism toward increasingly complex behavioral goals. Without the intervention of learned incentives, the process of shaping intricate patterns of behavior would be significantly hampered, if not impossible. For instance, training a service dog to perform a multi-step task, like retrieving medication, relies on the use of clicker training. The clicker, as a learned incentive, signals the correct approximation of each step, allowing the dog to gradually master the complete behavior sequence. The precision and speed of shaping are directly attributable to the conditioned reinforcing properties of the clicker.
The practical significance of this understanding extends to various domains, including education, therapy, and organizational management. In educational settings, teachers utilize praise, grades, and tokens as learned incentives to shape students’ academic performance and classroom behavior. These conditioned reinforcers provide feedback on progress and motivate students to persist in their efforts. In therapeutic contexts, token economies are employed to shape adaptive behaviors in individuals with developmental disabilities or mental health disorders. These token systems provide a structured means of reinforcing desired actions and promoting positive change. Furthermore, in organizational settings, performance bonuses, recognition awards, and other forms of positive feedback act as learned incentives that shape employee productivity and engagement. The understanding and application of these reinforcement techniques allows for the systemic encouragement of productive behaviors.
In summary, the capacity to shape complex behavior is intimately connected to the functional definition of learned incentives. The efficiency and effectiveness of shaping rely on the immediate feedback and consistent signaling provided by these secondary reinforcers. While the implementation of shaping techniques can be challenging, requiring careful planning and consistent application, the benefits are significant in promoting skill acquisition, behavioral modification, and overall well-being. Further investigation into the neural mechanisms underlying shaping and learned incentives has the potential to refine training and therapeutic interventions and enhance our understanding of how complex behavior is learned and maintained.
Frequently Asked Questions
This section addresses common inquiries and clarifies misunderstandings regarding learned incentives. The information presented aims to provide a comprehensive understanding of this phenomenon.
Question 1: How does a neutral stimulus become a learned incentive?
A neutral stimulus becomes a learned incentive through consistent association with a primary reinforcer. This pairing occurs repeatedly, such that the neutral stimulus begins to predict the occurrence of the primary reinforcer. This predictive association is what grants the initially neutral stimulus its motivational properties.
Question 2: Can a learned incentive lose its effectiveness?
Yes, learned incentives are susceptible to extinction. If the learned incentive is no longer consistently paired with the primary reinforcer, its predictive value decreases, and its ability to motivate behavior diminishes. Eventually, the learned incentive may cease to influence behavior altogether.
Question 3: Is the effectiveness of a learned incentive the same for everyone?
No, individual learning histories and contextual factors contribute to the variability in effectiveness of learned incentives. A stimulus that acts as a strong reinforcer for one individual may have little or no effect on another. The setting in which the incentive is presented can also influence its potency.
Question 4: What is the role of cognition in learned reinforcement?
Cognitive processes, such as expectancy, attribution, and evaluative judgments, play a significant role in modulating the effectiveness of learned incentives. An individual’s expectations regarding the likelihood of receiving the primary reinforcer, attributions for why a reward was received, and subjective evaluation of the reward all influence its motivational power.
Question 5: How are learned incentives used to shape complex behaviors?
Learned incentives are crucial for shaping complex behaviors because they provide immediate feedback during the process of successive approximation. Unlike primary reinforcers, which may be delayed or impractical to deliver consistently, learned incentives can be presented immediately after each correct approximation, guiding the organism toward the desired behavior.
Question 6: Are there ethical considerations involved in the use of learned incentives?
Yes, ethical considerations are paramount when using learned incentives, particularly in vulnerable populations. It is essential to ensure that the incentives are used fairly, transparently, and without coercion. Furthermore, the long-term consequences of using learned incentives should be considered, and efforts should be made to transition individuals to more natural reinforcers over time.
These FAQs highlight key aspects of learned reinforcement, emphasizing the role of association, extinction, individual differences, cognition, shaping, and ethics.
The next section will explore real-world applications of these concepts, demonstrating their relevance in various domains.
Effective Application of Learned Incentives
This section provides practical advice for leveraging learned incentives in various settings, based on principles of behavior analysis.
Tip 1: Establish Clear Associations: The effectiveness of a learned incentive hinges on a strong and consistent association with a primary reinforcer. When introducing a new learned incentive, ensure it is reliably paired with a reinforcing stimulus. For example, when implementing a token economy, clearly link tokens to desired rewards such as privileges or tangible items.
Tip 2: Use Immediate Reinforcement: Deliver the learned incentive immediately following the desired behavior. The shorter the delay, the stronger the association will be. For instance, in animal training, employ a clicker to mark the precise moment a desired action is performed, followed by a treat.
Tip 3: Vary Primary Reinforcers: To prevent satiation, periodically change the primary reinforcers paired with the learned incentive. This will help maintain the incentive’s motivational value. In a classroom setting, alternate the types of rewards students can earn with tokens, such as extra recess, choice of activity, or small prizes.
Tip 4: Fade Learned Incentives Gradually: As the target behavior becomes more consistent, gradually reduce the frequency with which the learned incentive is delivered. This fading process helps transition the behavior to being maintained by more natural reinforcers, such as social praise or intrinsic motivation.
Tip 5: Consider Individual Preferences: Recognize that not all incentives are equally effective for all individuals. Conduct preference assessments to determine which stimuli are most reinforcing for a given individual. This tailored approach maximizes the impact of the learned incentive.
Tip 6: Be Aware of Contextual Factors: The effectiveness of a learned incentive can vary depending on the environment. Ensure the incentive is appropriate for the context and that there are no competing stimuli that might diminish its value. For example, offering praise in a public setting might be more reinforcing for some individuals than others.
Tip 7: Monitor and Adjust: Regularly monitor the effectiveness of the learned incentive and make adjustments as needed. If the behavior is not increasing as expected, re-evaluate the pairing with the primary reinforcer, the immediacy of delivery, or the individual’s preferences.
These tips provide a framework for effectively applying learned incentives. Adhering to these guidelines promotes positive behavioral change.
The following section provides a conclusion of learned incentives.
Conclusion
This exploration of the mechanism by which neutral stimuli acquire reinforcing properties highlights the critical role of learning in shaping behavior. The principles surrounding this learning, when consistently applied, can effect targeted and predictable behavior change. The concept is a cornerstone of applied behavior analysis, informing effective interventions in clinical, educational, and organizational settings. A comprehensive understanding of the associative processes is vital for professionals seeking to promote adaptive behavior.
Further study of the intricacies of association, cognition, and individual differences will lead to more refined and effective applications. The ability to harness learning principles for the betterment of individuals and society presents a potent tool for behavioral scientists.
