The effectiveness of social reinforcement as a function of changes in rate of reinforcement

JOURNAL

OF EXPERIMENTAL

The Effectiveness of Changes

SOCJAL

PSTCHOL(GF

of Social

4, 123-142 (1968)

Reinforcement

in Rate

of Reinforcement1

M. BARON, ERNEST I,. ROBIXSOX,

REUBEN

Il’ayw

State

as a Function

AND STEPHEN

LAWRENCE”

lTnizvlvity

One, hundred and twenty subjects xere divitlc (1 into two groul~, receiving either 100% or 33% rcinforccment for the emission of the “correct” emotional-labeling response during an acquisition phase of 60 trials. This phase was followed by 60 trials during which conditions of none, or low change, modcrate change, and substantial change from the base-line rates were established, thereby giving us three positive-discrepancy groups and three negative-discrepancy groups of 20 subject,s each. Changes in the effectiveness of social reinforcement u-ere assessed by comparing, through the use of difference scores, the average number of correct responses made during the last two blocks of the shift phase with the average numbrsr of corrrct responses made during the last t,wo bloc~ks of the%acquisition seric>s.As hypothesized, a significant int,eraction b&wren the initial ratcx of rcinforccamrnt and amount of change was olr)taincd. A nc~gativc~ly accelrratctl linear trend was found for the 100:;b groups and a quadratic trend peaking at the moderate-c.hanpe level for the 33% groups. These results were interpretctl a.~ indicating the importance of direction as well as of thcl magnitudc~ of chnngp. Contrary to a second hypothesis, positi vi tv of subjrcrs mood changes was significantly affectccl onl? by ;n:tgnitu,ie of change. It ma;; also found that subjc(,ls who approval anti who I,nconnterc>tl a valued the espcrimrntcr’s substantial dccremr,nt in r&c, of a1)prov:tl xr’rc mor~r likely to }i(x rc~fiiFta:lt to extinction anll to voluntc,cxr for an unplcnsnnt (‘XI,;,rimcnt than ~(.r,’ th-ir ?ountPrparts who rc-rc,i\ ed a substanlial m ‘i’c ihr in ix:,, r)f approx al. Thee reactions we’re taken as supI,oriing (Ii<, notion. dcrivetl from the senior :author’s SW tllodrl, that, -ilbj<,c$s may 11,~ ingratiation tactics to rrduce dispsrif if? l,,,fwc,r n cllrrrnt :mrl ji:iGt lt,vels of rc~inforcc,mnnt.

The present study of the determinants of social-reinforcer effectiveness concerned with investigating subjects’ affective and behav-

is primarily

1 This research was supported by a grant to Ihr Crntrr for the St,udp of Cognitive Processes at Wayne State University by the Carnegie Foundation, and by research grant No. GS-1342 from the National Science Foundation to the senior author. The authors wish to thank Professor Samuel 8. Komorita and Irwin Katz for their helpful comments.

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BARON,

ROBINSOK,

AND

LAWRENCE

ioral reactions to social-reinforcer inputs that deviate in both degree and direction from experimentally manipulated base-line levels of social reinforcement. These variations in base-line levels are viewed as analogues of variations in past social-reinforcement history. The senior author (Baron, 1966) suggest’ed a model of the determinants of social-reinforcer effectiveness which assumed that the individual’s social-reinforcement history produces an internal norm or standard against which the adequacy of present social reinforcement is judged. This social reinforcement standard (SRS) is assumed to define a preferred region around which one seeks to secure future social reinforcement. Such standards may be viewed as techniques of interpersonal uncertainty reduction, allowing us to smoothly coordinate our actions and interactions even with unknown others. Substantial discrepancies from the SRS, whether in a positive or a negative direction, are assumed to produce considerable negative affect because the validity of one’s construal of the reinforcement properties of the environment is challenged.3 Such refutations may be equivalent to a threat to the self (Harvey, 1965, p. 249). Behaviorally, we expect that the introduction of uncertainty will lead the individual to increase the variability of his behavior in an attempt to ascertain what response pattern is likely to produce a rate of reinforcement that better approximates his SRS. Thus, the initial impact of a substantial discrepancy is likely to be a general decrease in level of performance. While we anticipate that the initial affective and behavioral impacts of a substantial discrepancy will be similar regardless of subjects’ previous reinforcement histories, we expect subjects with high and low standards of social reinforcement to show differential reactions to experimental events that follow any encounter with widely discrepant inputs. For example, if we assume that response variation by subjects results in their receiving fewer social reinforcements (assuming a contingent reinforcement procedure), then a differential state of affairs will occur for subjects with relatively favorable and relatively unfavorable social-reinforcement histories. A decreased frequency of reinforcement is more likely to satisfy subjects who initially experienced a low rate of approval, while it will fail to match the standards of subjects who initiahy experienced a high rate of approval. 3Bar~n (1966) suggests a number of reasons as to why substantial positive discrepancies may produce negative affect under certain conditions. For example, greater-than-expected levels of reward may produce negative affect because the person anticipates future disappointment and frustration for failing to be able to perform at a level commenmlratc with this higher-than-previously-attained level of reward.

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OF SOCIAL

REINFORCEMENT

125

Based on the above line of reasoning, it is hypothesized that subjects who encounter a substantial decrement in rate of reinforcement, as contrasted with subjects who encounter a substantial increment, will be more likely during subsequent experimental events to engage in behaviors designed to raise the experimenter’s rate of approval. For example, they will be more willing to keep giving the experimenter the “correct” response class even if he withdraws all reinforcement during an extinction phase. Furthermore, if the experimenter offers the subjects a further opportunity to ingratiate themselves by volunteering for an unpleasant future experiment, more of these subjects will be willing to volunteer (See Jones, 1964 for a general discussion of ingratiation). The use of such “ingratiation tactics” is predicted on the basis of Baron’s (1966) assumption that people are mot,ivated to engage in behaviors which they perceive will reduce subst,antial disparities between current levels of stimulation and some base-line level of stimulation. Finally, it should be mentioned that if the disparity is both substantial and of a prolonged duration, it may be expected that the person’s SRS will change. To the extent that such cognitive changes occur, disparity is reduced without the necessity fur behavioral adjustments of the type outlined above. The SRS and Differences in Reinjorcement History

While we have emphasized the importance of the SRS concept, we have not made any explicit statement as to how closely the SRS is likely to mirror the person’s actual social-reinforcement history. Baron (1966) assumed, for heuristic purposes, that the individual’s preference level would be isomorphic with the objective properties of his reinforcement history. ,4 more compelling position, we think, is to assume that for individuals who have previously encountered a high rate of social approval, inputs which are consonant, with this rate will be defined as appropriate and preferred. For individuals who have initially encountered a low rate of positive reinforcement, rates of reinforcement which are moderately abofv their objectively experienced rat? will be defined as appropriate a.nd preferred. Some

Related Areas of Investigation

Before stating the specific implications of the SRS model for a verbalconditioning paradigm, it may be noted that the present problem has relevance to at least three major areas of investigation. First, the developmental investigations of Gewirtz and his associa,tes (e.g., Gewirtz and Baer, 1958; Gewirtz, 1966) have long been concerned with the genera] issue of how variations in prior availability of a social reinforcer

126

BARON,

ROBINSON,

AND

LAWRENCE

affect its subsequent efficacy. Second, if t,he present problem is viewed as a special case of the general problem of how current and prior stimulus probabilities atiect response choice, it becomes relevant to the research that has been done in the probability learning tradition (see, for example, Estes and Straughan, 1954; Parducci, 1957; Stevenson and Weir, 1959). It should be noted, however, that almost all of the investigations done in this tradition have employed nonsocial stimuli which have relatively little affective loading (e.g., colored light.s, blank rards or not blank cards, marbles, etc.). Finally, it would appear that the present study has implicnt,ions for the general problem of how stimulus change affects emotional reactivity (e.g., the positivity of subjects’ moods, their liking for a given stimulus event, etc.). The essence of most models of this type (e.g., the “butterflycurve” hypothesis of McClelland, Atkinson, Clark, and Lowell, 1953) is their assumption that there is some optimum level of discrepancy beyond which both subjective preference and performance fall off. Past research suggests that where the stimulus series is low in affective loading, the optimum change is defined by some intermediate degree of disparity. This effect appears to occur regardless of the direction of the discrepancy (see for example, Haber, 1958). Harvey and Clapp (1965)) on the other hand, have recently demonstrated that when the stimulus series has affective significance (e.g., has relevance for a person’s selfevaluation), one must take the direction of the discrepancy into account. This conclusion is based on their finding that while even a slight negative discrepancy may produce negative affect, moderately large positive discrepancies produce positive affect. We may now specifically apply the present approach to a verbalconditioning paradigm. Implications

of the SRS Model

for T’erbal-Conditioning

Effects

Baron (1966) specifically focused on how changes in rates of social reinforcement might affect social reinforcer efficacy in the domain of verbal conditioning. A verbal-conditioning paradigm was selected because it offers an excellent situation in which to observe the effects of various discrepancy parameters on the subject’s behavioral adjustments as well as on his emotional reactivity. Furthermore, because the formal task requirements in this kind of situation are usually quite simple and the criteria for a ‘Lcorrect” response rather vague, it provides the subject with an excellent opportunity to manipulate the experimenter’s reinforcement behavior. That is, given a set of behaviors amenable to voluntary control, the rxprrimtnter’a ability to control a subject’s level of responding may

EFFECTIVENESS

OF SOCIAL

REINFORCEMENT

127

be importantly affected by whet,her the subject feels that his SRS is being met. Thus, the possibilities are provided for mutual social control, Hypotheses

If it may be assumed that individuals condition best at rates of reinforcement which they deem appropriate, and that one’s judgment as to what is appropriate is affected by his prior reinforcement history, the following hypotheses may be made. (a) There will be an interaction between variations in base-line rate of social reinforcement and the degree of change or discrepancy in determining conditionability, which has the following form: subjects who have previously encountered a low rate of social reinforcement will condition better with a moderately positive discrepancy in rate of reinforcement t,han they will with an extremely positive discrepancy, or a rat’e of reinforcement which matches their base-line rate, and subjects who have previously encountered a high rate of social reinforcement will condition better with a rate which matches this rate than at rates which are either moderately or widely discrepant. (b) It is also hypothesized that subjects’ affective reactions (e.g., changes in positivity of their mood) will be a complex function of the interaction between variations in base-line rate of social rcjnforcement and the amount. of change that subjects encounter on subsequent trials. The form of this int,eraction is assumed to follow the same pattern a,s that predicted for subjects’ condit,ioning behavior.

Subjects

The subjects were 120 femaIe undergraduates, predominantly sophomores, enrolled in Introductory Psychology classes at Wayne State University. The subjects were nonvoluntccrs who were randomly selected from the Int.roductory Psychology subject pool. Experimental

Task

A verbal-conditioning ta.sk was used which required that the subject judge the emotional state of a person from a facial photograph. The subject selected an (motional label from a list of six-love, joy, contentment, anger, fear, disgust. The labels represent two general response classes: positive and negative emotions. The task is presented to the subject as having a twofold purpose: (a) to validate a universal list of emotional categories developed by the experimenter (this instruction is designed to heighten the level of mutual interdependence that exists in the t~xperimPnter-subject relationship) ; and (bf to measure his social sensitivity by comparing his responses with norms obtained at the university (this instruction is designed to increase the ego involvement of the subject). The pictures used were f,aken from a past Wayne State University yearbook and were selected so as to be nc~utral in expression (i.e., pictures having obvious cues as to the emotional state

128

BAROX,

ROBINSON,

AND

LAWRENCE

were eliminated; this was done to break down any possible strong stimulus binding and, therefore, to make the subjects’ judgment,s particularly suscPptibl(’ to influence by the experimentrr’e rclinforcemcnts). Procedure

The following experimental procedure was then instituted. An operant series consisting of 15 nonreinforced trials was run. During this series, the experimenter showed the subjects 15 pictures, one at a time, giving them 10 seconds to make a judgment. The response class (i.e.. positive or negative emotional labels) that was least used during the operant series was designated the “correct” one for purposes of future reinforcement.4 After the operant series was completed and before the reinforcement treatments were given, the experimenter obtained the subjects’ estimates of how well they expected to do on this task. This procedure constituted our measure of generalized expectancy (GE). An acquisition series, for the building up of a social-reinforcement history, followed the operant trials. Subjects were randomly assigned to either a 100% or a 33% fixed-ratio contingent-reinforcement condition. The acquisition series involved 60 trials-four blocks of 15 trials at either of the two base-line rates. The administration of social reinforcement was accomplished by the experimenter’s saying “that’s good” or “that’s fine” for the correct response on one or the other of the above schedules.5 After the acquisition series was completed, the subjects were asked to estimate what proportion of judgments they expected to get correct on future trials. This constituted our situation-specific measure of expectancy (SE). The acquisition series was followed by a shift seties involving four more blocks of 15 trials each. During the shift phase, each of the original base-line groups was broken into three subgroups (20 subjects were randomly assigned in each group) in surh a way as to establish a condition of confirmation (i.e., low discrepancy), moderate discrepancy, and high discrepancy for the 100% and 33% Acquisition groups. respectively.’ Thus, the manipulated experimental variations produced thrr’r combinations of rate of rrwnrd involving negntivc discrepancies: IO@100 (low dis’ Mc& of the subjects (86%) showed a predominance of positive-labeling responses during the operant period. The subjects showing a predominance of negative-labeling responses were approximately equally distributed among the experimental conditions. ’ The role of experimenter was played by two different males: one a senior undergraduate, the other a second-year graduate student. However, the experimenter always introduced himself as a graduate student working on his master’s thrsis. The experimenters were always attired in a suit and tie. Each experimenter ran an equal number of subjects in each experimental condition. ‘The confirmation conditions (100-100 and 33-33) are designated “low discrcpancy” rather than “no discrepancy” because with a contingent reinforcement procedure there is always some disparity in the actual number of reinforcements the subjects receive. It should also be noted that what constitutes a large or a moderate discrepancy was determined arbitrarily and is roughly based on the kinds of magnitudes of stimulus change that have been effective in producing differential discriminations and choice behavior in studies of probability learning (see, for example, Parducci, 1957). We are presently attempting to improve on this procedure by having a control sample perform scaling operations on changes in rates of reinforcement (e.g., they inform us when they can discriminate small. medium, and large changes in rates of reinforcement).

FXFECTIVEh-ESS

OF SOCIAL

REISFORCEMEST

129

crepancy), KG-66 (moderate discrepancy), 100-33 (high discrepancy), and three combinations involving positive discrepancies: 33-33 (low discrepancy), 33-66 (moderate discrepancy), and 33-100 (high discrepancy). In order to add sensitivity to the design and to control on possible initial differences, variations in operant level were directly incorporated into the design as a blocks variable (High Operant Level= 4-7 “correct” responses on the operant series; Low Operant Level = O-3 of the to-be-reinforced response class on the operant trials). A discussion of the implications of this design for statistical analysis will be deferred until the Result,s section. Changes in so&Z-reinforcer efficacy. The major dependent variable to which this design was applied involved change scores based on differences between the average number of “correct” responses given by subjects during the last two blocks of the shift phase and the average number of “correct” responses (i.e., responses in line with the experimenter’s reinforcements) made during the ,last two blocks of the acquisition series. These “difference” scores constituted our basic measure of the changes in social-reinforcer effectiveness that were produced by changes in rates of reinforcement. Difference scores based on the terminal blocks in the acquisition and shift phases were utilized for two reasons. First, it was assumed that a certain degree of latency was required before the reinforcement procedures in each phase would have any stable psychological impact. Second, other studies involving changes in rates of reinforce.ment, such as Stevenson and Weir (1959), have also focused cm the terminal blocks in order to assess reinforcer effectiveness. For these reasons it was decided that other possible dependent measures, such as comparing the terminal blocks at acquisition with the first two blocks of the shift series, were likely to 1~1, both less sensitive and less appropriate. Experimental events following the shift phase. After the shift phase, an extinction series consisting of four blocks of 15 nonreinforced trials was instituted. The extinction series was run in order to gain some insight into the latency of subjects’ reactions to changes in rates of social reinforcement. The subjects were categorized as follows: a simple count was made, within each condition, of those subjects who manifested an increase in their emission of correct labeling responses during the extinction relative to their conditioning scores during the shift phase VS. those subjects who showed either no change or a drop in rate of conditioning. In our part.icular situation, the reduction of the extinction data to a nominal scale classification, although it involved the loss of information, seemed both more nppropriatc and more technically feasible than the use of a finer grain of analysis. A more powerful alternative procedure would have involved using the average number of correct labeling responses given during the last two blocks of the extinction phase as the dependent variable. Because of the plethora of experimental events that preceded these trials, t,he use of such a measurr would have necessitated a covariance analysis involving two or three covariates (e.g.. operant rate, number of correct responses after acquisition, and number of correct responses after shift). It seemed unlikely that we would be able to meet the strict assumptions of this more powerful design (e.g., linearity of all the regrcesion lines). The extinction phase concluded the experiment proper. An assessment period followed during which questionnaire and interview data were collected. The response format on the questionnaire involved both Likert-type items and scmantic-differential items using bipolar adjectives. Information was gathered concerning the subjects’ affective state during the esperiment and periods of possible shifts in mood. Data were also collected concerning how much the subjects really wanted the

130

BARON,

ROBINSON,

AND

LAWRENCE

experimenter’s approval, and their notions about the purposes of the experiment. The question concerning the extent to which the subjects wanted the experimenter’s approval served as a measure of the incentive &ue of the experimpnter’s reinforcements. The rcspons~ to this seven-point scalar item were Iltilizcid as follows: subjects were classified as assigning high incentive value if t,hey chpc,ked that they wanted the experimenter’s approval “to a very great extent,” “to a great extent,” or 20 a fair extent”; if they checked “to a small extent,” “to a very small extent,” or “not at all,” they were classified as giving low incentive value to the experimenter’s approval. Subjects who checked the middle category-“somewhat”were eliminated. The purpose of eliminating the subjects who checked the middle category was to create extreme groups on the variable of incentive value. It should bc noted that classifying subjects by means of a median-split procedure, and discarding subjects at the median, gave us essentially the same results. Just before the subjects were to depart, and after they had completed all the questionnaire materials, they were exposed to a situation designed to give us additional information as to the kinds of adaptive strategies that might develop in response to changes in rates of reinforcement. The same experimenter who served as the reinforcing agent asked the subjects if they would be willing to volunteer to take part in a future study involving the use of electric shock of at least moderate strength I‘. . . as a means of studying the relationship between anxiety .and learning.” The number of subjects volunteering for this “unpleasant experiment” .and the aforementioned categorization of the subjects’ extinction behavior ,constitutcd our major means of measuring delayed reactions to under- and oversewnrd conditions. RESULTS’

Creating Initial

Differences

Before presenting the effects of changing the rates of social reinforccment, it is necessary to establish the efficacy of our initial reinforcement treatments in creating an analogue of differences in reinforcement history. By the end of the first 60 trials, which comprised the subjects’ base-line social-reinforcement encounters, the 33% and 100% reinforcement groups reliably differed from each other in their emission of the ‘Lcorrect” response class. Analysis of variance of the mean number of correct responses emitted during the last two blocks of the acquisition series (Trials 31-60) reveals a statistically significant difference between these groups (F = 4.16, 1 and 118 df, p < .05). There were no statistically significant differences in operant level between these groups (F < 1). Furthermore, there were no reliable differences in mean number of correct responsesmade during the last two blocks of acquisition among the three subgroups which were to cotnprise the 100% AcquisitionDegree of Change groups and no reliable differences among any of the ‘All significance tests in this report are two-tailed unless otherwise specified. Findings at the .05 level or lrss will be regarded as statistically significant for the purpose of this report.

EFI’ECTIVEXESS

OF SOCIAL

REINFORCEMENT

131

three subgroups which were to comprise the 33% Acquisition-Degree of Change groups (Fs < 1). Given the fact that there are reliable behavioral differences between the 100% and 33% groups, the question now arises as to whether we have any evidence as to possible differences in cognitive structure between these groups prior to the shift series. One way of establishing such differences is to compare the subjects’ estimates of how well they expect to do on subsequent trials following their acquisition experiences for the 100% and 3370 conditions, respectively. If we have successfully cstablished differences in cognitive structure, we would expect subjects receiving a 100% reinforcement to expect to obtain a higher proportion of correct responses than would subjects receiving 33% reinforcement. That is, it is hoped that our differential reinforcement treatments will spread our subjects apart cognitively as well as behaviorally, thereby giving US a rough experimental analogue of differences in SRS. In order to control on initial differences in expectancy (i.e., differences in GE prior to any experimental reinforcement encounter), an analysis of covariance was performed on the expectancy estimates obtained immediately following the acquisition series (i.e., the SE measure). With GE controlled for, the adjusted expectancy score for the 100% conditions was 56.64; the adjusted expectancy score for the 33% conditions was 49.03. The analysis of covariancc reveals that these expectancy scores are significantly different in the predict,ed direction (F = 11.83, 1 and 117 dJ, p < .OOl). Thus, we may conclude t,hat subjects in the 100% treatment were reliably more optimist,ic about their chances of being correct than were subjects in the 33% treatment simply as a function of differences in their laboratory reinforcement experiences. Effects

of Changing

the Rate of Reinforcement

Acquisi.tion-shift difference scores.” In order to test the hypothesis that the cffcctirenear of a social reinforcer will be significantly influenced by the interaction between variations in initial rate of social reinforcement and the amount of change that subjects encounter during the shift series, an analysis of variance was done on the acquisition-shift difference scores. The analysis of variance involved a 2 X 3 X 2 factorial design (i.e., acquisition 100% vs. acquisition 33% ; high, medium, and low change from acquisition rate; and high vs. low operant level).9 Since the a An exploratory analysis of variance revcalcd that differencrs betwren ow two cspcrimenters neither nffcctcd the conditioning data as a main effect nor intcrsctrd significantly with our indrpendent variables (8’s < 1). “The introduction of operant level as a blocks variable created unequal Ns. Since there was not a significant departure from proportionality, an analysis-of-variance procrdure suggcstcd by Wincr (1962) for unequal but proportionate Ns ~xxs utilized.

132

BARON,

ROBINSON,

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LAWRENCE

average within-cell correlation for the 12 cells of this design (based on T to x transformations) between variations in acquisition rate of conditioning (final two blocks) and the present dependent variable (acquisitionshift difference score) was only .144 (T.~~ = .369), no attempt was made to control for a possible confounding due to differences in condit,ioning during the acquisition trials. As can be seen by an inspection of Table 1, there are two significant findings: a main effect for amount of change (F = 4.29, 2 and 108 df, p < 925) ; and a significant interaction between amount of change and acquisition rate (F = 3.90, 2 and 108 df, p < .025). Since any interTABLE

1

ANALYSIS OF VARIANCE OF ACQUISITION-SHIFT DIFFEREXCE SCORES AS A FUNCTION OF AMOUNT OF CH~XGE, VARIATIOHS IN ACQUISITION RATE, AED OPERANT LEVEL

source

df

ss

MS

change (C) Acquisition rate (A) Operant level (0) CXA

‘2 1 1 2

38.33 17 ‘,I.. 5”i

19.16 17 2.5’2

34.91

cxo OXA

'2

9.12 7.49 22.32

17.45 4.56

Amount of

CxAxO Within Total

(error)

1 2 10x 119

483.14

7.49 11.16

F 4.29* <1 <1

3.90* 1.02 1.68 2.50

4.47

598.00

* p < ,025. pretation of the main-effect finding for amount of change must be qualified by the Significant Change x Acquisition-Rate interaction, major attention will be devoted to specifying the nature of this interaction. The interaction data are presented graphically in Fig. 1. As can be seen from Fig. 1, the essenceof the Change X AcquisitionRate interaction is that the positive-discrepancy groups, going from low to high, rise for moderate change and then return to the same level. On the other hand, the negative-discrepancy groups go straight down. These differential reactions of the 100% and 33% Acquisition groups to the change conditions can be most precisely specified by means of a trend analysis. The significance of linear and quadratic trends was tested for the 100% and 33% groups, respectively. For the 100% group a significant linear trend was obtained (F = 10.83, 1 and 108 df, p < .005), while the quadratic trend was insignificant (F < 1). Just the reverse pattern was found for the 33% acquisition group. That is, the quadratic trend was

EFFECTIVENESS

OF SOCIAL

-----33%

Acquisition

-100%

Acquisition

Rate Rote

Low Amount

Of

Change

FIG. 1. Amount of Change X Acquisition on differences between the last two blocks blocks of the shift series).

133

REIXFORCEMENT

High

Med In

Rate

Of

Social

Bate interaction of the acquisition

Reinforcement (change series

scores were based and the last two

significant (F = 5.34, 1 and 108 df, p < .05) while the linear trend was not (F < l).l” Further insight into the role played by direction of shift may be obtained from the results of the following selected comparison. A comparison between the combined positive-discrepancy conditions (3366 and 33-100) and combined negative-discrepancy conditions (100-66 and 100-33) reveals that subjects in the positive-discrepancy conditions tended to show a greater increase in the number of correct labeling responses than did subjects in the negative-discrepancy conditions (F = 3.14, 1 and 108 df, p < .lO). Mood change. In an attempt to delineate some of the processes underlying the effeck of changes in rate of social reinforcement, information ‘“It should also hr noted that a drljendent measure involving the differences in level of responding bctwecn the last two blocks of the acquisition phase and thr first two blocks of the shift series was investigated. While the ordering of thesr difference scores yielded change functions which were identical to those obtainrd with comparisons based on only the terminal blocks of each phase (i.e., a quadratic trend for the 33% group, and linear trend for the 100% group), for this analysi?:. only the linear trend was significant. This failure of significance is due largely to the greater variability found in the measure based on the first two blocks of thp shift series as compared with scores based on the two terminal blocks. This finding supports our previous assumption (of the Method section) that changes in rate of reinforcement reqllire a certain amount of time to become generally effective.

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was gathered concerning the subjects’ affective states.” Of most direct relevance to our concern is the subjects’ responses to a series of postexperimental questions concerning their evaluations of (‘mood” change. A screening question first asked the subjects to indicate whether they had experienced a change in mood. If they answered yes to the question (86 of 120 affirmed that they had), they were then instructed to indicate whether the mood change was from positive to negative or from negative to positive.12 In order to relate these responses to the amount and direction of reinforcement change, a three-way chi-square analysis was performed. It involved amount of reinforcement change (high, medium, low), direction of change (positive vs. negative), and t,ype of mood TABLE FREQUENCY

DISTRIBUTION BY AMOUNT

2

FOR CHI-SQUARE AND DIRECTION

ANALYSIS OF MOOD OF CHANGE

Amount High Direction of change Positive Negative Totals

&I+ 0 3 9

CHANGE

of change

Medium hl-

>I+

LOW nr -

31+

M-

0

d

6

9

11

11

(i

n

5 6

20

16

12

1X

11

Note.-M+ = mood change from negative to positive; M= mood change from positive to negative. Positive direction of change in reinforcement corresponds to the change cells involving 33y0 Acquisition subjects, while negative change in reinforcement refers to the change cells involving the 100% Acquisition subjects.

change (negative to positive vs. positive to negative). The frequency distribution for this chi-square analysis is presented in Table 2. In order to test for possible interaction effects, the chi square was partitioned according to a procedure described by Sutcliffe (1957). The results of this analysis are presented in Table 3. As can be seen from an inspection of Table 3, t,he only significant effect is an interact-ion of amount of reinforcement change and mood change (x2 = 6.434, 2 d,f, p < .05). The form of this interaction is quite clear: as discrepancy increases from low to medium to high, the proportion of subjects showing positive mood I’ The questionnaire included open-ended and Likert items on mood change. In addition, the subjects were asked to describe their affective state on bipolar scales (e.g., nervous-calm, comfortable-uncomfortable, happy-sad, etc.). The bipolar items yielded data which were less consistent than the data obtained by asking the subjects directly whether their mood changed in a positive or a negative direction. l’A chi-square analysis of the relationship between a reaction of no change and t.he experimental treatments revealed tfhat thrrc was no signifiennt arsoeintion (x” = 2.87, .30 > p > .20).

EFFECTIVENESS

OF SOCIAL

135

REIYFORCEMENT

shifts declines and the proportion of subjects showing negative mood shifts increases. Both of the high-discrepancy cells (100-33, 33-100) seem to lead to an increment in negative affect despite the fact that in one case the subjects encountered a substantial decrease in rate of reinforcement, while in the other case they encountered a substantial increase. Thus, it would appear that affective change is a function of the amount of reinforcement change; direction of reinforcement change does not affect mood change either as a main effect. or as an interaction component. TABLE

3

PARTITION OF &I-SQUARE FOR BY AMOUNT AND DIRECTIOX

Source A (amount) A (amount) D x ptl AXDXN Total

X M (mood change) X D (direction1

MOOD CHANGE OF CHANGE 4f

XS

2 2 1 ‘7 7

6.434* !a3 ,000 1.921 0.277

* p < .05.

Delayed measures of the effects of changes in rates reinforcement: some “ingratiation effects.“13 In the introduction, it was suggested that a possible delayed effect of a substantial decrease (e.g., from 100 to 33%) in the rate of reinforcement would be the instigation of behaviors designed to please the experimenter, and t.hereby to raise the frequency of his reinforcements. It was further suggested that such effects would be most pronounced for those subjects who strongly desire the experimenter’s approval. When subjects do not desire the experimenter’s approval, they are not likely to show an interest in behaving in a manner designed to please him, particularly when they are under-rewarded (e.g., are dropped from 100 to 33% rate of reinforcement). Indeed, they are likely to become progressively more negativistic in their behavior. “‘Thr data to be prrsented below involve a good deal of selectivity. Therefore, the rcadrr is cautioned to view these findings as only suggestive. We felt that such selectivity was justified in order, to help us pick up differences in coping strategy which might bc quite subtle. Thus, it was decided at this stage of our research program to focus on estrcme groups. The comparisons in this section are restricted. therefore, to the 100-33 and 3%100 groups. Data were collected and analyzed for the other conditions and, as we might expect, differences between these groups were levs clear cut (e.g., both the 33-66 and lo&66 groups failed to manifest the relationship between incentive value and resistencc to extinction that appeared in the lo@-33 group) (sr(‘ Fig. 2).

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When subjects are subjected to a substantial positive increment in reinforcement (e.g., the 33%-100% subjects), we expect a lack of a consistent relationship between their desire for the experimenter’s approval and the instigation of behavior designed to please him. In the absence of a social-reinforcement deficit, individual differences in the incentive value of the experimenter’s reinforcements are assumed to be less crucial in mediating the subjects’ behavior than the fact of overreward per se. That is, over-reward should lead to a general decrease in behaviors designed to please the experimenter. The delayed effects of under- and over-reward for the log-33 and 33-100 conditions, respectively, were assessed by the use of two separate dependent-variable measures: a resistance-to-extinction categorization, and the number of subjects volunteering for the “shock” experiment. The distribution of 100-33 and 33-100 subjects who assigned high and low

No Change or @ecreo% I” Condltloning Durmg ExtInction

Incentive FIG.

2. Reactiolls

of subjects

in

Value

the

100-33

Of E’s

and

Reinforcement

33-100

condit,iolls

to extinction.

incentive value to the experimenter’s reinforcement,, is presented in the form of frequency polygraphs for resistance to extinction (Fig. 2) and for volunteer behavior (Fig. 3). (See the Method section for a discussion of the basis on which the subjects were dichotomized on incentive value.) Because the cell frequencies were in some cases below 5, these data were analyzed by means of Fisher’s Exact Test, which is a one-tailed test of significance. A remarkably consistent pattern emerges for both the “resistanceto-extinction” and the “volunteering” data. Under tEle 100-33 condition,

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subjects who value the experimenter’s approval highly are more likely than subjects who do not value the experimenter’s approval to: be resistant to extinction (Fig. 2), and volunteer for an unpleasant experiment (Fig. 3). The p values were <.05 and <.lO, respectively, by Fisher’s Exact Test. The 33-100 subjects, on the other hand, show no consistent pattern of relationship between incentive value and variations in resistance to extinction and volunteering behavior (p < .70 and p < .50 for the extinction and volunteering data, respectively).

9

100-33

33-100

8f

VOlUtlteer

q

Non-Volunteer

k Hi

Incentive

FIG.

3. Volunteering

behavior

Value

of

Of E’s

subjects

in

Reinforcement

t)he

100-33

and

33-100

conditions.

A comparison across conditions of only those subjects who highly value the experimenter’s approval reveals that while seven out of nine of the high-incentive-value subjects within the lo@-33 condition are willing to volunteer for an unpleasant experiment, only one out of five of the highincentive-value subjects within the 33-100 condition show such an inclination (t = 2.57, p e .Ol). The resistance-to-extinction data are in the same direction (six of nine vs. two of five), but fail to reach statist,ical significance. DISCUSSION

Before examining the major findings of this study, a brief discussion of our research strategy seems in order. As we have previously indicated, it has been assumed that by providing our subjects with evaluative feedback in the form of different rates of verbal approval, we could create an analogue of variations in past reinforcement history. In order to heighten the psychological significance of what, at best, was a transitory laboratory experience, we selected a behavior to reinforce-the subjects’

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emot’ional-labeling responses for which there was not likely to be any clear-cut past reinforcement history. Furthermore, it was assumed that the acquisition phase should function in a manner analogous to a naturalistic social-reinforcement history in generating a,n SRS. This reasoning was based on the prior assumption that in an ambiguous situation, one’s initictl evaluative experiences will exert a powerful influence on one’s reactions to subsequent evaluative inputs. In essence, then, we were assuming that a prir~~~ effect would occur. In order to test the above assumption, we provided for two kinds of measures of the subjects’ implicit standards: a generalized-espectancy (GE) measure before any reinforcement was received, and a situationspecific-expectancy measure following the acquisition and shift phases. Our findings arc supportive of the not’ion that we were able to crcnte differences in cognitive structure by varying the subjects’ initial reinforcement encounters. With subjects’ GEs controlled for statistically, we were able to obtain highly significant differences between t’he 100% and 330/o conditions in their estimates of how well they expected to do on future trials, Furthermore, additional statistical analyses involving changes in cxpectanry cstimntes demonstrated that expectancies formed after the acquisition phas:c were riot significant.lp chnngctl by subjects’ subsequent reinforcement experiencrs. Conditioning

Ejfects

Two significant effect,s were obtained: (a) a significant main effect of amount of change in rate of reinforcement, and (In) a, significant interaction of differences in base-line rate and amount of change. The main effect was largely accounted for by the fact that large discrepancies or changes, regardless of their point of origin, produced a decrement in level of responding. The significant interaction, on the other hand, reflects the fact that consonant and moderately discrepant inputs had cliffering effects depending on the subjects’ base-line rates of reinforcement. This interaction is reflected in a negatively accelerated linear t:,end for the 1OOyO group and a quadrat.ic trend peaking at, the moderate tliscrepnney level for the 335% group. These findings are supportive of the modified version of the senior author’s SRS model of social-reinforcer cffectireccss, stnted cnrlier in this paper. This modification involves the assumption that. :I person’s SRS will be set at a level which is isomorphic with the objective properties of his social-reinforcement history only for individuals who have previously encountered a high rate of approval. Persons who have previously rncountcrcd a low rate of approval may allow their reinforrcmerit standard to hc biased by considerations involving hope (see Hnrvey

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and Clapp, 1965), and therefore set their SRS equal to a rate of approval which is moderately above their base-line level. While the findings, that 100% subjects show t,hcir highest level of responding with a consonant rate of approval and 33% subjects show their greatest responsivity with moderate positive discrepancies, are consistent with this interpretation, additional data are needed to suhetantiate this position. An independent measure of subjects’ SRSs mu& be obtained for groups known to differ in object,ive-reinforcement history. The assessment of subjects’ SRSs should go beyond the kind of expcctancy measures obtained in this study and get at the proportion of responses that subject.s hope to get correct and/or feel t’hcy should or ollght t#o get correct. Such rcscarrh is presently underway. Ingxdiation

Tactics

The present results provide fresh insights into the kinds of strategies that subjects with different kinds of social-reinforcement histories might develop in response to marked changes in rates of reinforcement. While the immediate impact of a substantial discrepancy was a general decrease in rate of conditioning, as measured by changes in rate of conditioning from the acquisition to the shift phase, subjects in the 100% Acquisition group manifested different coping strategies on subsequent experimental events than did subject,s in the 335% Acquisition group. The subjects in the 100-33 condition who strongly valued t.he experimenter’s approval were more resistant to extinction as well as more willing to volunteer for an unpleasant experiment than were subjects who assigned low incentive value to the experimenter’s approval within the same condition. Within the 33-100 condition, on the other hand, subjects who assigned high incentive value to the experimenter’s approval performed no differently from subjects who assigned low incentive vsluc. Furthermore, a comparison across conditions of the subjects who gave high incentive value to the espcrimenter’s approval revealed that. subjects mit’hin the IO&33 rendition were significantly more willing than wcrc subjects within the 33-100 condition to I-olunteer for an ~lnplewnnt, future experiment. These findings would Fecm to support Baron’s (1966) notion that subjects are motivated to perform in a manner likely to correct substantial disparities from their preferred levels of rcinforrcmc>nt. Implications

for n Discrepancy

Model

of Social-Reinfower

The present results would appcnr to have ccrtnitj cations. The finding that large discrepancie?, regardless product a relat,ive decrement in rate of conditioning

Efjects

thcorctical impliof thtsir direction, fits t.hc model of

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McClelland et al. (1953). The importance of the direction of change, however, seems clearly indicated by the interaction of base-line rate and amount of change. This latter finding is supportive of Harvey and Clapp’s (1965) position that when the stimulus series has affective significance, the direction of the discrepancy, as well as its magnitude, is an important determinant of the behavioral and affective outcomes. It should be noted, however, that our behavioral data are not strictly applicable either to McClelland’s discrepancy theory of hedonic value or to the aforementioned study of Harvey and Clapp, because those authors, while implying behavioral implications, focused their predictions on a pleasant-unpleasant dimension of subjective experience. A second reason why the present data cannot be unambiguously related to the magnitude-discrepancy issue is more serious: the present design confounds direction of change with differences in initial level of reinforcement. That is, while it is tempting to say that our behavioral databoth immediate and delayed-demonstrate that direction of change is implicated along with amount of change in determining subjects’ behavioral adjustments to discrepancy, such an interpretation is somewhat hazardous since our discrepancy conditions do not originate from a common base-line rate of reinforcement. This confounding, however, was a necessary consequence of our interest in exploring how ma&e&/ different antecedent conditions may affect the efficacy of current socialreinforcement schedules. That is, the choice of a 100% Acquisition group to contrast with a 33% group meant that we had created a situation where it was impossible to have both negative and positive discrepancies of varying degrees for each of the acquisition groups. We are presently tackling this confounding problem as follows: subjects are uniformly given a 50% rate of approval during acquisition. Two shift groups are then created in a positive direction (75%, loo%), and two in a negative direction (25%, 00%). While the present condit,ioning data arc supportive of the notion that direction of change is important when the st,imulus series has evaluative significance, the findings regarding affect,ive reactions do tend to support t.he McClelland-type model of stimuIus change, which disregards direction. That is, the positivity of subjects’ affective reactions is significantly affected only by amount of change, with the Large-Discrepancy conditions producing considerably more negative mood change than the Moderate- and Low-Discrepancy conditions. It should be noted, however, that the Low-Discrepancy conditions did not produce t,he kind of “negative affect of boredom” that the McClelland model would lead us to expect. They produced, inst’ead, mood changes that were similar to those found in the Moderate-Discrepancy conditions.

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141

The failure to find evidence for importance of direction of change in the affect data is inconsistent with the results obtained by Harvey and Clapp (1965) as well as with our own hypothesis that changes in affect should parallel changes in rates of conditioning. This divergence in results may reflect the fact that, an induction using changes in rate of social reinforcement may be more indirect (i.e., ambiguous) in its evaluative implications than Harvey and Clapp’s procedure of giving subjects discrepant feedback concerning another’s evaluation of their personal characteristics. The more indirect the evaluative implications, the greater the room for defensive reactions (e.g., denial, distort.ion, etc.) which may wash out the effects of direction of discrepancy. In this connection, it should be noted that in the present study the authors found that changes in expectancy following shifts in rate of reinforcement were more veridical for the Positive- than for the Negative-Change conditions (see also Rosenhan and Messick, 1966, concerning subjects’ tendencies to underestimate the occurrence of negative inputs having evaluative connotations). In conclusion, while the present findings do not offer definitive support for the SRS model, they do demonstrate that the kind of discrepancy parameters suggested by the model importantly affect subjects’ affective and behavioral reactions in a verbal-conditioning paradigm. REFERENCES R. M. Social reinforcement effects as a function of social reinforcement history. Psychological Review, 1966, 6, 527-539. ESTES, W. K., AND STRAUGHAN, J. H. An analysis of a verbal conditioning situation in terms of statistical learning theory. Jownal of Experimental Psychology, 1954, 17, 225-234. GEWIRTZ, J. L. Deprivation and satiation as setting conditions determining the reinforcing efficacy of non-appetitive (social) stimuli. Paper presented at the first Minnesota Symposium on Child Psychology, May, 1966. GEWIRTZ, J. L., AND BAER, D. M. Deprivation and satiation of social reinforcers as drive conditions. Journal of Abnormal and Social Psychology, 1958, 57, 165-172. HABER, R. W. Discrepancy from adaptation level as a source of affect. Journal of Experimental Psychology, 1958, 56, 37&375. HARVEY, 0. J. Cognitive aspects of affective arousal. In S. S. Tompkins and C. E. Izn.rd (Eds.), A.fect, cognition and personality. New York: Springer, 1965. Pp. 242-263. HARVEY, 0. J., AND CLAPP, W. F. Hope, expectancy, and reactions to the unexpected. Journal of Personality and Social Psychology, 1965, 2, 45-52. JONES, E. E. The psychology of ingratiation. New York: Appleton, 1964. MCCLELLAND, D. C., ATKINSON, J. W., CLARK, A. R., .~KD Tmmr.~, E. L. The achiewcment motive. New York: Appleton, 1953. PARDUCCI, A. Alternative measures for the discrimination of shift in reinforcement ratio. rlmerican Journal of Psychology, 1957, 70, 194-202. BARON,

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S. Affect and expectation. Journal of Personality and 1966, 3, 38-44. STEVENSON~ H. W., AND WEIR, M. W. Variables affecting children’s performance in a probability learning task. Journal of Experimental Psychology, 1959, 6, 403-412. SUTCLIFFE. J. P. A general method of analysis of frequency data for multiple claesification designs. Psychological Bulletin, 1957, 54, 134-137. WINER, B. J. Statistical principles in expetimentcrl design. New York: McGrawHill, 1962. ROSENHAN,

Social

D.,

ROBINSO?i,

AND

MFSSICK,

Psychology,

(Received January 27, 1967)