xperimental analysis of the behavior of persons in …

Behavior and Social Issues, 24, 111-125 (2015). © Isis Gomes Vasconcelos & João Claudio Todorov. Readers of this article may copy it without the copyright owner’s permission, if the author and publisher are acknowledged in the copy and the copy is used for educational, not-for-profit purposes. doi: 10.5210/bsi.v.24i0.5424

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EXPERIMENTAL ANALYSIS OF THE BEHAVIOR OF PERSONS IN GROUPS: SELECTION OF AN AGGREGATE PRODUCT IN A METACONTINGENCY1

Isis Gomes Vasconcelos João Claudio Todorov

Universidade de Brasília

ABSTRACT: An experimental procedure was designed to analyze group behavior. This procedure was compatible with the basic definition of metacontingency: two persons behaving in a coordinated manner to produce an aggregate product. Positive consequences are produced based on the prescribed characteristics of the aggregate product. A chessboard-like table comprising 64 squares was projected on a computer screen, and knights (white and black) were positioned at opposite corners of the board. The players moved the knights one at a time. The goal was to end the trial with the knights positioned on adjacent cells of the table (aggregate product). In experiment 1 an ABCB design was used. In the A (baseline) conditions, no consequence followed the trials (extinction). In the B conditions, the words “Congratulations. You win” appeared when the knights met within the boundaries established as the aggregate product for that trial. In the C conditions, the words “End of trial. Try again” appeared in all trials. In experiment 2 an ABAB design was applied. The variability of the sites selected by the participant in successive trials was used to measure the effect of the selecting consequences. “Congratulations. You win” predicted narrow adherence to the criterion for the aggregate product, while signalized extinction (“End of trial, try again”) resulted in variability in the selected sites. KEYWORDS: metacontingency, aggregate product, selection by consequences, social behavior, humans

Behavior analysis is a science of conditional relations developed both through experimental analyses of individual behavior and interpretation of behavior in natural environments based on the concept of contingency. Its foundations were established by a seminal work, “The Behavior of Organisms” (Skinner, 1938), a theoretical language made after a sequence of laboratory experiments. In “Science and Human Behavior” (Skinner, 1953) concepts advanced before were used to interpret human behavior in social situations involving cooperation, competition, sharing, etc., and even social movements at the cultural level. In its simplest form, social behavior involves two persons, the behavior of one being antecedent or consequent to the behavior of the other (Skinner, 1953, p. 297). Social behavior is part of a metacontingency when such interlocked behavioral contingencies result in an aggregate product selected by the cultural environment. (Glenn, 1986, 2010; Houmanfar & Rodrigues, 2006; Malott & Glenn, 2006).

1 This work is based on a Master’s Dissertation presented by Isis Gomes Vasconcelos to the Programa de Pós-Graduação em Ciências do Comportamento, Departamento de Processos Psicológicos Básicos, Instituto de Psicologia, Universidade de Brasília. João Claudio Todorov is Professor Emeritus and Research Associate of the Universidade de Brasília and Bolsista de Produtividade Científica 1D (CNPq, Brazil). E-mail: [email protected]

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Studies exploring this new concept have relied on adaptations of classical experiments, such as those performed by Wiggins (1969) and Hardy (1968/2009), procedures that make behavior analysis more similar to other behavior sciences, as the works of Baum, Richerson, Efferson, & Paciotti (2004) and Rachlin et al. (e.g., Yi & Rachlin, 2004) show. Such procedures also address the complaints made by critics that the theory of metacontingency lacked substance without previous experimental analyses (e.g., Branch, 2006; Marr, 2006). However, as Skinner (1950) pointed out in “Are theories of learning necessary?” theory building profits more when through induction we go from more simple to more complex arrangements. Experimental analysis of group behavioral processes should follow the guidelines established for the experimental analysis of individual behavior (e.g., Skinner, 1938; Ferster & Skinner, 1957; Sidman, 1960). The published literature has generally used complex procedures (e.g., Vichi, Andery & Glenn, 2009; Smith, Houmanfar & Louis, 2011; Costa, Nogueira & Abreu-Vasconcelos, 2012; Tadaiesky & Tourinho, 2012; Ortu, Becker, Woelz, & Glenn, 2012). It appears to be appropriate to call such works experiments on metacontingencies because the concept seems to be as inclusive as the operant (e.g., Catania, 1973; Todorov, 2002), but those procedures involve metacontingencies embedded in more complex arrangements.

The aim of the present work was to find a dependent variable and an experimental environment more amenable to the examination of the effect of individually manipulated independent variables. The definition of metacontingency implies that discriminative stimuli and reinforcement for individual behavior should be provided reciprocally by the behavior of others, that such interlocked behavioral contingencies should result in an aggregate product and that the consequences should be contingent on the characteristics of (at least) the aggregate product (Glenn, 2010). Besides, the minimum number of persons working together should be two.

Experiment 1

Method

Participants. Ten students from the University of Brasília (three males and seven females) volunteered to participate in the experiment. Participants were recruited via invitations extended during introductory psychology classes and had no research experience. The Oversight Board of the University of Brasília previously approved the research project.

Apparatus. In order to carry out the activity it was used a LG notebook with AMD processor, Duron ™, 857 MHz, 128 MB of RAM memory, and Microsoft Windows seven ultimate system equipped with the “2cavalos” software developed by Todorov, Vasconcelos & Costa (Vasconcelos, 2014). The software generates a virtual chessboard and two pieces, the Knights of a chess game, and allows piece movements by touches or mouse clicks in the cell which will receive the piece. The software also generates an output with the registry of time duration of each trial, the number of movements per player and the player’s position after each trial.

Setting and procedure. Pairs of students participated in the experiment independent of other couples. The experimental setting was a room furnished with a large table and three chairs. The software’s interface displayed a virtual chessboard and two chess pieces located in the upper right and lower left corners of the board as shown in Figure 1.

THE BEHAVIOR OF PERSONS IN GROUPS

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Figure 1. Software interface After being seated in front of the computer, the participants read and signed an agreement

stating that they understood and were willing to perform the experimental task. They also completed a questionnaire for participants’ characterization. Next, they received the following instructions:

Hello!

You will now complete an activity together. Each player will have only one piece, the knight from the chess game. You will move the pieces across the chessboard using the touch pad. To move the piece, click twice above the cell that should receive the piece. The Knight moves in an “L” shape, two cells forward and one to the side in any direction. This is the only way of moving the piece. Each trial begins with each piece located at opposite corners of the chessboard. The player who owns the piece in the upper square always moves first. Players move their pieces one after another and are not allowed to skip a move. Each trial ends when the two pieces meet each other on the chessboard by being moved to adjacent cells in one of three configurations: a side-by-side meeting, a diagonal meeting or a top-bottom meeting. The initial trials allow you to practice. After the practice stage, you will receive a message at the end of each trial. This message will either be, “CONGRATULATIONS! YOU WIN” or “END OF TRIAL. TRY AGAIN”. You can talk during the game. Your goal is to win as often as possible.

Any questions?


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Choose who is going to control each piece on the chessboard.

Are you ready to start?

These instructions were the only information delivered. Any questions asked before or during the session were answered by directing participants to the written instructions. The consequences of reaching the aggregate product varied across the experimental conditions:

Baseline (A) Phase 1: When the knights met at any two adjacent squares, the trial ended and a new trial

began. No message was shown. The baseline condition ended after 10 trials. Shaping 1 (B) Phase 2: (64 cells). For seven trials, when the knights met at any adjacent squares, the

message “You win!” appeared and a new trial began. Phase 3: (36 cells). In this phase, the lateral cells on all four sides of the matrix were out-of-

bounds. The inner 36 cells were in-bounds. If the knights met on any two adjacent cells, the message “Congratulations! You win!” appeared and a new trial began. Aggregate products that included at least one of the out-of-bounds cell resulted in the message “End of trial. Try again.” Trials continued until the knights met in any two of the 36 inner cells for seven consecutive trials.

Phase 4: (16 cells). In this phase, two rows of lateral cells on all four sides of the matrix were out-of-bounds. The inner 16 cells were in-bounds. If the knights met on any two adjacent cells, the message “Congratulations! You win!” appeared and a new trial began. Aggregate products that included at least one of the out-of-bounds cells resulted in the message “End of trial. Try again.” Trials continued until the knights met in any two of the 16 inner cells for seven consecutive trials.

Phase 5: (four cells). In this phase, only the central four cells were in-bounds. If the knights met on any two adjacent cells within bounds, the message “Congratulations! You win!” appeared and a new trial began. Aggregate products that included at least one of the 60 out-of-bounds cells resulted in the message “End of trial. Try again.” Trials continued until the knights met in any two of the four inner cells for seven consecutive trials.

Signalized Extinction (C) Phase 6: In this condition, participants were given twenty trials in which the negative

feedback message (“End of trial, try again”) appeared on the screen if the knights met in any two adjacent cells on the 64-cell board.

Shaping 2 (B) Phases 1 to 4 of Condition Shaping 1 (B) were repeated (reshaping). After receiving seven

consecutive positive feedback messages in Phase 10 of Condition Shaping 2 (B), the participants received the following message: “That is all. Thanks for participating.”

No extra information was provided to the participants, that is, they were not aware of the out of bounds areas, its changing criteria or any other signal indicating contingencies shifting. The events and the time that elapsed during and between the events were recorded. A complete set of these records is available upon request. The major dependent variable in this study was a


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measure of variability or dispersion. When the definition of aggregate product includes all 64 cells, every meeting of the two knights is followed by positive feedback. From what is known from operant experiments (e.g., Antonitis, 1951), repetition of reinforced trials might lead to diminishing variability in location of meetings, and extinction trials should result in increased variability of cell occupancy. By successively diminishing the area defining aggregate product for the metacontingency it was expected that at the end of trials the knights would repeatedly occupy the cells within that area, and that with the suspension of the conditional relation variability would increase again.

In any phase of n trials, two knights may occupy 2n cells as meeting places. The dependent variable was the number of cells actually occupied in the last seven trials of each experimental condition [Baseline (A); Shaping 1, Phase 5 (B); Signalized Extinction (C); and Shaping 2, Phase 10 (B)] divided by the number of cells that could be used: 14 (2 knights x 7 trials). A ratio of 1.0 indicated that in 7 trials, 14 different cells were used; the minimum ratio was 2/14 = 0.1429 (if the knights always met at the same two cells of the 14 possible cells).

Variables of interest. During analysis, three variables of interest were observed: the meeting location, defined here as the aggregated product; the trial duration and the number of movements. The last two were considered as possible measures of stereotypy, a byproduct of reinforcing operant behavior that might occur with aggregate products as results of interlocked behavior contingencies.

Results

Table 1 shows the number of trials undergone in each experimental condition by each of the five sets of participants. The number of trials required to advance to a new condition varied from 7 [Shaping Condition (B) with feedback] to 20 [Signalized Extinction condition (C)]. The minimum number of trials required to end the session was 7 (Phases 2 and 7, necessarily). The maximum number of trials was 186 (Phase 5, pair AB).

Figure 2 shows the ratio of the number of cells actually used to achieve an aggregate product (adjacent cells where the knights met) to the maximum number of cells that could be used in seven trials [2 (knights) X 7 (trials) = 14]. Dispersion measures for the five sets of participants tended to be high in both the Baseline (A) and the Signalized Extinction (C) conditions (closer to 1.0 than to 0.1429). However, they tended to be low in both Shaping (B) conditions (closer to 0.1429 than to 1.0). The pattern of variability in the Baseline and Signalized Extinction conditions and the high concentration in the Shaping 1 and 2 conditions were similar across all five sets of participants.

No statistically significant differences were found between the data from conditions A and C or the Shaping 1 and Shaping 2 (B) conditions (t = 0.584, p = 0.590 and t = 1.632, p = 0.178, respectively). However, comparisons between the Baseline and Shaping 1 and between the Signalized Extinction and Shaping 2 conditions did show statistical significance (t = 3.935, p < 0.017 and t = 6.971, p < 0.002, respectively). A partial eta squared comparison within the interventions yielded an effect size of 0.829, which indicates the strong effect of the training situation between conditions.


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Table 1. Total number of trials per phase for each pair from Experiment 1. Phases 1, 2, 6 and 7 had a fixed number of trials. All of the other phases ended after a sequence of 7 criteria-matched trials. Condition Phase AB CD EF GH IJ

Baseline 1 10 10 10 10 10

Shaping 2 7 7 7 7 7

3 7 7 12 7 11

4 24 10 7 12 30

5 186 29 94 82 174

Extinction 6 20 20 20 20 20

Reshaping 7 7 7 7 7 7

8 7 7 7 11 7

9 7 17 13 7 7

10 16 43 14 19 51

Figures 3 and 4 also show that trial duration and number of movements per trial tended to be lower in shaping phases than in baseline and signaled extinction phases. This effect may be explained by a lesser control of the behavior of participants by the previous behavior of its partner after successive trials end in extinction. Extinction of individual behavior within the interlocked behavior contingency should generate variability, with more movements (and consequently larger trial duration) before the knights would meet.

Four out of five pairs showed shorter trials during shaping phases when compared to baseline and signalized extinction phases. Except pair IJ, which showed the reduction trend in shaping 1 but not in shaping 2. During baseline and signalized extinction, the highest mean was 59ʺ for pair CD and the lowest was 10ʺ for pair AB. During baseline and signalized extinction, the pair IJ had the highest trial duration, 25ʺ and the pair AB had the lowest with 7.4ʺ in average.

Pairs CD and EF showed a slight trend toward reduction in the number of movements during shaping phases in comparison to baseline and extinction phases. Pairs AB and GH showed a reduction trend comparing Extinction and Shaping 2 phases but not between Baseline and Shaping 1 phases. Pair IJ showed higher means during shaping phases contradicting the expected trend. The majority of the pairs ended each trial with four or five movements, the lowest number of movements observed. The highest number of movements was nine for pair CD during Shaping 1 phase. During Baseline and Signalized Extinction, the lowest number of movements per trial was four for pair AB and the highest number of movements were 10 for pair GH.


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Fig. 2. Number of occupied cells divided by the total number of cells that could have been occupied in

Experiment 1 for each pair in phases 1, 5, 6 and 10, respectively.

Discussion

The results presented here show, for five sets of two participants, that the consequences programmed by the metacontingency affect the variability of the aggregate product location. Interlocked behavioral contingencies were responsible for the movements of the knights across the chessboard, resulting in an aggregate product: the meeting of the knights on adjacent cells of the board. With no special consequences programmed for that meeting or when signalized extinction was the consequence, the variability of the aggregate product location was high. When the consequence was positive feedback (“Congratulations! You win!”), the aggregate product location converged to the target defined by the metacontingency.

The procedure confirmed the repeated occurrence of an empirical aggregate product produced by interlocked behavioral contingencies. Besides, it demonstrated that the condition B effects were due to the independent variable manipulated.

Experiment 2

Method

Participants. Ten students from the University of Brasília (four males and six females) volunteered to participate in the experiment. Participants were recruited via invitations extended during introductory psychology classes and had no research experience.


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Figure 3. Trial duration (seconds) mean of the last 7 trials in phases 1, 5, 6 and 10 for each pair.


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Figure 4. Number of movements per trial for the last 7 trials in phases 1, 5, 6 and 10.


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Procedure. The procedure was identical to that used in Experiment 1, except that the C

experimental condition was replaced by a repetition of the baseline (A) condition. The design for Experiment 2 was ABAB. The written instructions also remained the same, except that in the phrase “The initial trials allow you to practice”, the term “the initial” was replaced with “some”.

Results

Table 2 shows the number of trials undergone in each experimental condition by each of the five sets of participants in Experiment 2. The number of trials required to advance to a new condition varied from seven (Phases 2 and 7, necessarily) to 10 (Phases 1 and 6). The minimum number of trials required before the session was considered completed was seven (Phases 3, 8 and 9; pair KL), with a total duration of 1.57 min on average. The maximum number was 92 (Phase 9; pair QR). Figure 5 shows the ratio of the number of cells actually used to achieve the aggregate product over 14, the maximum number that could be reached. Dispersion measures for the five sets of participants tended to be high for both Baseline 1 and Baseline 2 (closer to 1.0 than to 0.142) and low in both Shaping (B) conditions (closer to 0.142 than to 1.0).

Table 2. Total number of trials per phase for each pair from Experiment 2. Phases 1, 2, 6 and 7 had a fixed number of trials. All of the other phases ended after a sequence of seven criteria-matched trials. Condition Phase KL MN OP QR ST

Baseline 1 10 10 10 10 10

Shaping 2 7 7 7 7 7

3 7 8 7 23 13

4 18 34 14 7 49

5 27 42 71 42 51

Extinction 6 10 10 10 10 10

Reshaping 7 7 7 7 7 7

8 7 7 7 9 8

9 7 18 10 92 9

10 12 15 25 51 12


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Figure 5. Number of occupied cells divided by the total number of cells that could have been occupied in Experiment 2 for each pair in phases 1, 5, 6 and 10.

The pattern of variability in the Baseline conditions and the high concentration in the

Shaping conditions were similar across all five sets of participants. No statistically significant differences were found between the data from the Baseline conditions or between the data from the Shaping conditions (t = 2.049, p = 0.13 and t = -1.732, p < 0.182, respectively). Comparisons between the Baseline 1 and Shaping 1 and between the Baseline 2 and Shaping 2 conditions, however, showed statistical significance (2 (t = 13.874, p < 0.01 and t = 5.176, p < 0.014, respectively). A partial eta squared comparison within interventions yielded an effect size of 0.943, indicating the strong effect of the training situation between conditions.

All the pairs showed a trend to shorter trials during shaping phases in comparison to baseline phases (Figure 6). In the absence of feedbacks, the highest mean was 39ʺ for pair LK and the lowest was 12ʺ for pair QR. During shaping, the highest mean lasted 14ʺ for pair MN and the lowest had 4.8ʺ of duration for pair OP.

All the pairs showed a systematic trend to less movement during shaping phases in comparison to baseline phases (Figure 7). Only four movements were made during each trial of shaping phases. The lowest number of movements during baseline phases were five (QR) and the highest were 22 (pair ST).


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Figure 6. Trial duration (seconds) mean of the last seven trials in phases 1, 5, 6 and 10 for each pair.


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Figure 7. Number of movements per trial for the last seven trials in phases 1, 5, 6 and 10.

Discussion

Experiment 2 was a systematic replication of Experiment 1 (Sidman, 1960): it resulted in the repeated occurrence of an empirical aggregate product produced by interlocked behavioral contingencies and selected by its consequences (e.g., Glenn, 2010). The results also showed a reversal of the effect of such consequences on aggregate product location. For all five sets of


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participants, location variability increased or decreased according to the programmed conse-quences.

In the present experiments, Signalized Extinction and Baseline return had similar effects upon response variability. It was expected, since both contexts lead to an elimination of the response-reward relationship.

General Discussion

The procedure followed the usual demonstration of shaping of an operant with low relative frequency of occurrence: initial determination of operant level followed by differential reinforcement of successive approximations to the target response (Keller & Schoenfeld, 1950).

Groups do not behave. “Group behavior” is the result of individuals behaving in groups (Skinner, 1953). As Locey & Rachlin (2013) have noted, “reinforcement of the fittest actions replaces survival of the fittest organisms as a selection process” (p. 245). Therefore, selection of cultural practices defined by aggregate products may replace composition of the fittest groups at the cultural level (Skinner, 1981; Baum, 2005). As with biological and behavioral evolution (Locey & Rachlin, 2013, p. 245), variation and reproduction (repetition) in cultural evolution occur in the context of environmental antecedents and interlocked behavioral contingencies, with aggregate products selected by consequences provided by a cultural selecting environment (Glenn, 2004, 2010; Glenn & Malott, 2004; Malott & Glenn, 2006; Houmanfar, Rodriguez & Ward, 2010).

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