In the study by Harte et al. (2018), the degree of bypass was directly manipulated by different amounts of training. In a recent unpublished study conducted by our research group, we maintained constant derivation and investigated the influence of consistency on persistent compliance. Consistency has been manipulated by the systematic use of feedback, based on the assumption that manipulating corrective feedback would affect the degree of consistency (e.g., providing feedback for “correct” derived responses would likely increase consistency). In two experiments, all participants were first trained on the same set of basic relationships as in Harte et al. (A-B/B-C). What followed this basic training was then distinguished by experiences. In Experiment 1, participants were then trained to the same basic relationships for two other experimental blocks, one group receiving feedback on their performance and another group receiving no feedback on performance. However, after the basic training in Experiment 2, participants were tested directly for derived A-C relationships for two other experimental blocks. Again, half of the participants received feedback on their performance, the other half did not.
Thus, while the derivative was always kept constant as in Experiment 1, it was tested directly in Experiment 2 (i.e., participants were given the opportunity to derive relationships instead of simply being reformed to basic relationships). Therefore, the degree of derivation of Experiment 2 was in principle lower than that of Experiment 1 and was evaluated in a distinct but related way (i.e.: Re-education of baseline relationships with and without feedback versus testing derived relationships with and without feedback). Participants in both experiments then completed the MTS emergency switching task. One difference between rules and contingencies is that of knowledge. To understand the rules, we need to learn the rules and memorize them, and then learn when to apply them. Contingency behavior is learned because of the reinforcement or punishment to which the individual is subjected by his actions. Your future actions will be modified in a way based on this previous experience of reinforcement and punishment. While men have a certain level of decency in the workplace, they are judged less harshly for what they wear. The consequences for a woman who does not respect decency in the workplace are much greater than for men, resulting in discrimination based on gender.10 Early research on reinforcement plans with human participants, showing that response rates were consistently high or low during an FI schedule, can easily be interpreted in terms of relational networks generated by a person`s contact with contingencies. For example, imagine a participant who gave only one or two responses in the first study according to an FI schedule, compared to a participant who gave a large number of responses. It seems likely that these separate interactions with contingencies would create two different relational networks. In the first case, the network would likely contain references to time rather than response rate, while the second network would contain references to response rate rather than time.
In both cases, the consistency of the relational network would likely increase, as responding in accordance with that network would result in strengthening. Of course, the consistency of the “response rate network” would be compromised if a participant spontaneously stopped responding for a period of time during one of the FI studies (because an amplifying agent would be distributed for the first response emitted after the interval). In this sense, high-speed performance would not be considered “insensitive” to the unexpected, but rather would reflect the relative consistency of a relational network induced by the unexpected. Alternative theories emerged in the 1960s, focusing on the individual facing a decision. Game theory narratives understood that it wasn`t just about the individual making an isolated decision to avoid discrediting them – it was also that we expected everyone else to do the same. We put the fork on the left side of the plate not because it is appropriate, but because it is what we expect from others and because we want to follow the rules of the game.5 It is not always rational to do so, as it may not serve our self-interest, but our desire to cooperate and get along with others. takes precedence. Related research has focused on the extent to which molded specifications (e.g., “quick press” to find the right button) matched or contrasted with molded emergency descriptions (e.g., button works “after random number of presses”); Matthews, Catania and Shimoff, 1985). Especially during schedule interruptions, participants were asked to complete rate sheets, as in Catania et al. (1982). Researchers reported that the design of SOPs resulted in responses that were consistent with descriptions rather than timelines.
However, the design of the emergency descriptions resulted in a response that was on schedule but not as well as molded descriptions. Overall, these studies have shown that it is useful to functionally distinguish verbal behaviour that occurs before and during exposure to a schedule from performance on the schedule itself. In hindsight, the realization that a rule (or instruction) is a reasonable concept and lacks a clear functional and analytical basis was a serious problem, at least for behavioral analysis. Or more specifically, although the researchers tried to functionally identify different classes of rule-based behavior (e.g., pliance and tracking), there lacked a clear functional definition of what it means for a rule to specify a contingency. When the work of Sidman and colleagues on equivalence relations solved the problem of specification (i.e. exactly how rules specify contingencies; see below), this could be seen as an indication of the original lack of functional-analytical precision in the concept of the rules themselves. Perhaps for this reason, research on period-based behaviour seemed to be overshadowed by research on stimulus equivalence (see below). The remaining half of the paper will examine the relationship between rule-based behavior and derived stimulus relationships and the impact of this relationship on further development in this domain.
behavior that is generally accepted as normal and correct At this point, it seems important to emphasize that the 20 intersections identified in the HDML framework are the units of experimental analysis, while the planes and dimensions themselves are not. For example, although it is possible to say that mutual involvement is the bidirectional relationship between two stimuli, mutual involvement can only be analyzed experimentally by specifying one or more of the dimensions. As mentioned earlier, the relationship being tested must match the relationship trained in a given way (e.g. if X is greater than Y, then Y is less than X), and the number of derived relational responses must be specified (for example, a participant must generate at least 8 out of 10 responses, indicating that Y is indeed less than X if there is no programmed gain or other feedback). Many studies have shown that presenting different stimuli and/or tasks during IF schedules tends to induce non-human performance (i.e. wavy patterns). Such a finding does not necessarily indicate that stimuli and/or tasks provided functionally identical contingency-sensitive services to those observed in animals. For example, presenting a digital clock counting seconds to the end of an FI calendar could have been used to generate a relational network that controlled behavior that topographically resembled non-human performance. In fact, the relational network now included a reference to the output of the clock as a source of behavior control (e.g., “Keep checking the timer before responding”).
To the extent that this particular network helped the participant to evaluate the length of the interval, the coherence of the network would increase and its derivation would decrease as the experimental session progressed.