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MIAMI UNIVERSITY The Graduate School

Certificate for Approving the Dissertation

We hereby approve the Dissertation

Meghan K. Housley

Candidate for the Degree:

Doctor of Philosophy

______Director Heather M. Claypool

______Reader Kurt Hugenberg

______Reader Amy Summerville

______Graduate School Representative Lawrence B. Nadler

ABSTRACT

THE POWER OF CRYPTOMNESIA: INTERPERSONAL POWER AND INADVERTENT PLAGIARISM

By Meghan K. Housley

Plagiarism arouses intense emotions in and out of academic settings. Relatively recently, it has been suggested that not all cases of plagiarism are intentional, and that they may instead be due, at least sometimes, to unconscious influences of memory in which the plagiarized information is incorrectly experienced as novel and self-generated (e.g., Taylor, 1965). Such inadvertent plagiarism (IP) is known as cryptomnesia, which is argued to be due to failures during source monitoring, namely, failing to accurately identify whether the source of information is internal or external (e.g., Johnson, Hashtroudi, & Lindsay, 1993). Asymmetries in power have been shown to influence the degree to which individuals engage in careful processing of sources, with high power individuals processing others superficially and low power individuals processing others carefully (e.g., Fiske, 1993; Goodwin, Gubin, Fiske, & Yzerbyt, 2000). Thus, high power individuals should plagiarize more than non-powerful others. In two experiments, I manipulated power and the timing of this manipulation (occurring before or after an interaction), and then assessed rates of IP. The results of Experiment 1 suggested that high power increases rates of IP, though only when instantiated before an interaction. Experiment 2 yielded only null findings. Implications of the former and possible explanations for the latter findings are discussed.

THE POWER OF CRYPTOMNESIA: INTERPERSONAL POWER AND INADVERTENT PLAGIARISM

A DISSERTATION

Submitted to the Faculty of

Miami University in partial

fulfillment of the requirements

for the degree of

Doctor of Philosophy

Department of Psychology

Meghan K. Housley

Miami University

Oxford, Ohio

2010

Dissertation Director: Heather M. Claypool

CONTENTS

INTRODUCTION ...... 1 Power...... 4

EXPERIMENT 1 ...... 6 Method...... 6 Participants and design...... 6 Procedure ...... 6 Results...... 7 Dependent measures and scoring...... 7 Analysis of errors...... 9 Analysis of the Remember-Guess-Know data...... 10 Discussion...... 11

EXPERIMENT 2 ...... 12 Method...... 12 Participants and design...... 12 Procedure ...... 13 Results...... 14 Discussion...... 15

GENERAL DISCUSSION ...... 15

REFERENCES ...... 19

APPENDIX...... 21

TABLES ...... 23

FIGURES...... 29

TABLES

1. Mean proportions of generation errors made as a function of power level and power timing (Experiment 1). Separate tables for error type: Self, Other.

2. Mean proportions of intrusion errors made as a function of power level and power timing (Experiment 1).

3. Mean proportions of RKG responses as a function of power level and power timing. Separate tables for response type: IP, Intrusions, Hits.

4. Mean proportions of generation errors made as a function of power level and power timing (Experiment 2). Separate tables for error type: Self, Other.

5. Mean proportions of intrusion errors made as a function of power level and power timing (Experiment 2).

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FIGURES

1. Proportions of inadvertent plagiarism responses as a function of low, medium, and high power when presented before encoding and after encoding (Experiment 1).

2. Proportions of inadvertent plagiarism responses as a function of power level when presented before and after encoding (Experiment 2).

3. Proportions of inadvertent plagiarism responses as a function of power level when presented before and after encoding, with participants that explicitly noted suspicion of “partner” removed (Experiment 2).

ACKNOWLEDGMENTS

I would like to thank my advisor, Heather Claypool, for her many contributions at every stage of this project and throughout the entirety of my graduate education. I would also like to thank the members of my committee, Kurt Hugenberg, Amy Summerville, and Lawrence Nadler, for their valuable advice on this project. It has been both a privilege and a pleasure to work with each of them. I also offer many thanks to my friends for their constant encouragement and inspiration. Last but not least, I would like to thank my family, Stephen, Helen and Matthew Housley for their support in all of my endeavors.

The topic of plagiarism arouses intense emotions both in and beyond academic settings; at a minimum, it is something frowned upon and, often times, it can provoke severe penalties. The disdain held for the plagiarizer may stem from the perception that the individual was not willing to put in the effort necessary to formulate his or her own ideas and that he or she actively intended to pilfer someone else’s work. However, relatively recent research has posed the possibility that plagiarism may not be, at least under some circumstances, a deliberate attempt to take another’s work, but rather may be an inadvertent act. Such a notion has been suggested regarding Helen Keller (Bowers & Hilgard, 1986) and Nietzsche (Jung, 1905/1957), who have both been charged with plagiarizing others. In our own field of psychology, Freud (1901/1960) admitted that his idea for bisexuality was something that he thought was original, but was actually a colleague’s idea. Skinner (1983) even commented on such an occurrence in his own work by saying, “… one of the most disheartening experiences… is discovering that a point you have just made – so significant, so beautifully expressed – was made by you in something you published a long time ago” (p. 242). Though Skinner makes reference here to plagiarizing himself accidentally, the focus of my dissertation will be on the inadvertent plagiarism of others, as it is this type of plagiarism that is considered most problematic. Thus, subsequent references to inadvertent plagiarism will refer to unintentionally claiming others’ work as one’s own. In scientific language, cases of alleged inadvertent plagiarism (IP) have been termed experiences of cryptomnesia – unconscious influences of memory that cause thoughts to be incorrectly experienced as novel (e.g., Taylor, 1965). 1 One explanation for cryptomnesia is that it is due to failures in source monitoring: “the processes involved in making attributions about the origins of memories” (Johnson, Hashtroudi, & Lindsay, 1993, p. 3; see also Macrae, Bodenhausen, & Calvini, 1999). When we engage in the type of monitoring most relevant in cases of IP, we are attempting to determine whether something had an internal or external source (Johnson & Raye, 1981; Johnson, Raye, Foley & Foley, 1981). More specifically, we need to determine if we generated the information or if someone else did. Successful source monitoring is determined by (1) the attributes of the memory representation and (2) the decision processes used to determine that representation’s origin (Johnson et al., 1993). Memory-representation attributes refer to various cognitive operations, sensory/perceptual details, contextual cues, semantic details, and affective reactions present during encoding. When these attributes are highly differentiated across memories, less source confusion occurs and there are fewer source monitoring errors. Or, put another way, when the attributes of one memory are similar to the attributes of another memory, assigning source is more difficult, resulting in more source errors. For example, let us consider a case in which someone is trying to make a vacation destination decision and is seeking guidance from two sources: a friend and a travel agent. One of these individuals suggests Greece as a great spot. If

1 Some may believe that cryptomnesia is merely a case of source amnesia in which the information is recalled but the source of the information is not. In source amnesia studies, participants are typically provided with information during a learning phase, followed by a cued recall phase in which the original items are intermixed with other, novel items. As each item is recalled, participants are asked to identify where they learned that information. If they identify the source of the information incorrectly, source amnesia is said to have occurred. Though this sounds similar to cryptomnesia, a vital difference between the two exists. With cryptomnesia, the information is perceived as original, whereas with source amnesia, the material is recognized as unoriginal though the source cannot be identified (Brown & Murphy, 1989; Schacter, Harbuck, & McLachlan, 1984). In each case, the context surrounding the information is forgotten, though the experienced originality of the information is different.

our target spoke to the travel agent at his office and the friend at her home, there is likely to be minimal source confusion about who suggested Greece. However, if the target spoke to the agent and friend both in the same restaurant, there may be greater confusion over the source of the information because the contextual cues are less differentiated. Thus, if the target remembers receiving the suggestion of “Greece” while in the restaurant, the context alone does not provide him with any information that could help him determine whether the source was the friend or the agent. Additionally, source-origin decisions are usually made in a quick and heuristic fashion using perceptual information, providing greater potential for errors to be made. Thus, the less carefully one ponders the source-origin decision, the more likely it is one will make a mistake. Failures in source monitoring are suggested to be the mechanism by which cryptomnesia occurs. Though in the previous example a target person was trying to determine whether the source (of Greece) was his friend or his travel agent, individuals may, at times, get confused regarding whether the source is another person or is the self. Indeed, the first laboratory demonstration of cryptomnesia provided some initial evidence of the importance of source monitoring in this phenomenon. Namely, Brown and Murphy (1989) investigated cryptomnesia in four-person groups, asking each member of the group to generate exemplars of categories in turn. Categories were either semantic (e.g., sports, musical instruments) or orthographic (e.g., words beginning with “BE,” “FO”). In the generation phase, the participants were simply to provide an exemplar of the given category (e.g., “tennis” if “sports” was the category) without repeating any that had been previously provided. Next, participants engaged in a written recall task in which they were to recall only the exemplars they had provided during the generation phase (termed the “recall-own” task). Finally, participants were asked to generate completely novel exemplars of the category that were never provided during the generation task (termed the “recall-new” task). In these initial studies, cryptomnesia was most evident during the generation phase (that is, participants did frequently provide an answer that had been generated earlier by themselves or another person) and during the recall-own task (that is, participants frequently “recalled” answers that they believed were originally generated by the self but had actually been provided by other participants). Analyses also revealed that participants were more likely to plagiarize the responses that were uttered immediately before them on any given round. Brown and Murphy suggested that, within each round, participants were likely thinking about their next contribution, and therefore not paying attention to the exemplars provided most recently, which resulted in the inadvertent plagiarizing of them. Indeed, the source-monitoring account of cryptomnesia argues that when an individual does not devote sufficient attentional resources to the information provided by others, source errors will occur. Later work on cryptomnesia more carefully examined the processes at play in the different phases of the Brown and Murphy (1989) paradigm. Specifically, Landau and Marsh (1997) explained that all three phases (the generation task, the recall-own task, and the recall- new task) require the participant to correctly differentiate old versus new items. However, only the recall-own task requires source monitoring. To explain, during the generation and recall-new tasks, the participants need only to provide words without repetition. Therefore, they only need to monitor if a potential word had been said before. In these cases, the source of the material is meaningless. If an answer is old, it does not matter whether it was generated by the self or another person. In either case, it is an inappropriate response. During the recall-own task, however, participants must identify if a word is old or new (e.g., was it actually provided in the generation phase) and must identify the source of that word. That is, once a word has been

identified as old, participants must engage in additional processing to make a source identification (i.e., Did I say it, or did someone else?). In their studies, Landau and Marsh (1997) increased plagiarism in the recall-own tasks (but not the generation tasks) by making it harder to distinguish between self and other. During the generation task, played with a computer, some participants were shown the computer’s responses in their entirety. However, others were shown the responses one letter at a time and were told to guess the computer responses. These participants were very involved with the computer’s responses and, ultimately, could have “generated” the computer’s response themselves as they tried to guess any given word. Through this greater involvement with the computer’s responses, later source monitoring became more difficult and plagiarism increased. Based on the source-monitoring account, any factor that makes it difficult to differentiate between the self and another as the source of information should increase inadvertent plagiarism. Using this logic, Macrae, Bodenhausen and Calvini (1999) investigated whether increasing the similarity between the self and a partner might increase rates of plagiarism. In it, participants played an orthographic category generation game in same- or mixed-sex pairs (female-female or female-male pairs). The authors found that there were greater instances of other-plagiarism in the same-sex, as opposed to the mixed-sex, pairs. As stated previously, during the recall-own phase, participants must first identify if a word was previously provided (recognition) and then determine the source of that word (self or other). Macrae and colleagues argued that when one’s partner is perceptually similar to the self (as is the case in the same-sex pairs) that source monitoring is more difficult. In other words, female participants were more likely to correctly identify that a word was provided by their male partner than by their female partner. Once a word had been successfully recognized as old, the greater differentiation between the self and the male partner allowed for greater source-monitoring accuracy and less inadvertent plagiarism. In another study, Macrae and colleagues (1999) manipulated whether one’s partner was present or not during the recall task. The authors reasoned that when the partner was not present, fewer source-related cues would be present, making differentiation of self versus other information more difficult. Supporting this logic, participants were more likely to plagiarize when their partner was absent. In a final study, these same authors examined whether cognitive distraction might increase rates of plagiarism. To do this, a radio excerpt was played simultaneously during the generation task for some of the pairs but not the others. The authors argued, “Because source monitoring depends upon the quality of stored memorial representations, anything that prevents perceivers from binding memory details to one another, and to the memory trace itself, should promote source confusion…Thus, factors such as stress, distraction, and alcoholic inebriation…should all attenuate perceivers’ source-monitoring performance” (p. 284). Consistent with this reasoning, higher rates of IP were observed for those who were distracted during the exemplar generation task than those who were not. Thus, these studies (by Macrae et al., 1999) show that a variety of factors that make source monitoring difficult result in greater rates of cryptomnesia. That is, when source monitoring errors are likely, participants will be especially likely to believe that other people’s efforts are their own. Based on the above review of the literature, it is clear that cryptomnesia is a fascinating topic, but one that has received relatively little attention. Given that source-monitoring errors seem to be the driving force of inadvertent plagiarism, it is surprising that more social- psychological variables have not been identified as moderators of the phenomenon, as many social-contextual factors have been shown to increase or decrease the degree to which perceivers

attend to and process other people (sources) in the environment. If source monitoring does play a role in acts of IP, then social-psychological factors that influence how we deal with sources may encourage or attenuate rates of IP. One such factor is power.

Power People often find themselves in situations of asymmetrical power, that is, in situations in which they have greater or lesser “capacity to modify others’ states by providing or withholding resources or administering punishments” (Keltner, Gruenfeld, & Anderson, 2003, p. 265-266). Typical examples are found in employment (boss versus subordinate) and classroom settings (teacher versus student), as well as many others (e.g., the military). Social-psychological research has shown that those in positions of power often exhibit different cognitive and behavioral patterns of responses than those in positions of powerlessness (e.g., Stevens & Fiske, 2000). For the purposes of the current research, the most interesting difference between the powerful and the powerless is in how they attend to others in their environment. According to power-approach theory (Keltner, Gruenfeld, & Anderson, 2003), over time power creates an approach orientation, which directs attention toward the rewarding outcomes of that power. Thus, it appears that people naturally orient themselves toward those in power when benefits are possible (Gruenfeld, Inesi, Magee, & Galinksy, 2008). In addition, asymmetrical outcome dependency theory (Dépret & Fiske, 1999; Fiske & Dépret, 1996) proposes that people have a basic need for control. When people are in a position of power, they already have control and, as a result, have no need to afford extraneous effort processing others’ deeply. In other words, they do not have the motivation to dispense effort when not absolutely required. Conversely, those who have little power are motivated to restore control in whatever way possible. This may manifest itself as more systematic processing of the situation, compared to the relatively heuristic processing of those with power. Supportive of these theoretical perspectives, empirical work has shown that the powerless attend closely to the powerful, whereas the powerful pay fairly superficial attention to the unique attributes of the powerless (e.g., Fiske, 1993; Goodwin, Gubin, Fiske, & Yzerbyt, 2000). For example, Goodwin and colleagues (2000) found that powerless participants paid substantial attention to the counter-stereotypic information about powerful others, whereas the powerful participants paid substantial attention to stereotypic information about powerless others. Additionally, low-power (subordinate) primates look at and focus on high-power (dominant) others more than the reverse (Chance, 1967). Similarly, low-power individuals are more likely to look at others while listening than while speaking, whereas those high in power are no more inclined to look toward others while listening than they are when speaking (Dovidio, Ellyson, Keating, Heltman, & Brown, 1988). Thus, it appears that having power predisposes individuals to focus only superficially on those that have less power. Given the differences between those in power versus the powerless in terms of source processing, it seems reasonable to believe that such differences might impact rates of cryptomnesia. As stated previously, deficits in source monitoring have been suggested to be the mechanism by which cryptomnesia occurs, and as we have seen, power differentials have the potential to influence the degree to which one considers sources. Specifically, because high- power individuals pay attention to others in only a superficial manner, they may not carefully “bind” their partner’s contributions to the proper source (Macrae et al., 1999) during an interaction (i.e., during encoding), and thus they may engage in more IP than those with less power. Interestingly, if differential binding is the reason why high- and low-power participants

differ in their rates of IP, then the timing of the power induction could be of great importance. Specifically, if high power is not instantiated until after an interaction with a partner (and thus after whatever natural level of source “binding” has occurred), power may not have an influence on IP. That is, if high-power perceivers have the correct source attribution information available, they may use it and avoid higher rates of IP. If this logic is correct, then those feeling powerful during an interaction (during encoding of a partner’s contributions) should be more apt to later engage in IP than those with less power. However, those who feel powerful after an interaction (after encoding) should be no more inclined to plagiarize than those with less power. On the other hand, inadequate source binding may not be the only reason why high- power perceivers might engage in greater rates of IP. High-power people may have the correct source information at their disposal but, consistent with asymmetrical outcome dependency theory (Dépret & Fiske, 1999; Fiske & Dépret, 1996), they may not take the time and effort necessary to use that information and provide accurate (non-plagiarized) responses. This lack of motivation may be due to seeing others (and thus their responses) as a “means to [their] own ends” (Keltner et al., 2003, p. 272) or perhaps, they may not recognize the necessity to stop and think about the source information. That is, when asked to reproduce their own contributions and avoid their partner’s (during a recall-own task), a high-powered person may have an accessible response come to mind and simply jot it down without scrutinizing its source carefully (or at all). Thus, it is a possibility that, even with appropriate source encoding, feeling powerful may still lead to greater levels of IP. If this lack of motivation to consider the source decision drives IP, then instantiating high power before or after the interaction could increase IP. Thus, when power is instantiated before an interaction, high power may both inhibit careful source “binding” and trigger a lack of motivation to consider the source decision at the time of retrieval. When the power is instantiated after an interaction, high power has no ability to influence source binding, but it still could quash motivation to consider the source decision. If a lack of motivation alone is what drives high-power individuals to engage in greater rates of IP, the results in the before- and after- encoding conditions should be identical, with higher power participants engaging in more IP than those with less power. On the other hand, if inadequate source binding alone is what drives high-power individuals to engage in greater rates of IP, then high-power individuals should plagiarize more than those low in power, but only if the power is instantiated before encoding. Finally, if both processes (poor source binding and lack of motivation to consider the source decision) contribute to IP, then high power individuals will engage in more IP than will low power individuals in both the before and after encoding conditions, but the effect would be larger in the before condition. Two experiments will test whether having power increases rates of IP and whether the timing of the power induction (before versus after encoding) moderates this effect. In both experiments, participants will play a game with a computer in which they will have to alternate generating words within four categories, later having to recall only the words that they themselves provided. In Experiment 1, power will be instantiated by using a writing prompt in which participants are to recall a situation in which they had more, equal, or less power than someone else. In Experiment 2, power will be instantiated by informing participants that either they or their “partner” (actually a computer) will later get to determine which person gets to do a fun task versus a boring task. Overall, I expect high-power participants to engage in more IP than either low (Experiment 1 and 2) or medium (Experiment 1) power participants. Moreover, if poorly binding sources to their contributions is the only reason why high power individuals engage in IP, then this effect will occur only when power is in place during encoding. If low

motivation to consider the source decision is the only reason why high power individuals plagiarize, then this effect will occur equally in both the before and after encoding conditions. If both processes are in play, the effect will emerge in both conditions, but will be statistically larger in the before encoding condition.

Experiment 1

Method Participants and design. Participants were 120 (60 female, 3 unknown) Miami University students enrolled in PSY111 who received partial course credit in return for their participation. Fourteen (7 female, 1 unknown) participants were removed for not completing the tasks correctly. The study was a 3 (power level: high, medium, low) × 2 (power timing: before encoding, after encoding) between-subject design. Procedure. Participants arrived at the lab in groups of 1 – 6 and were greeted by a female experimenter. Each participant was seated in a private cubicle and completed the informed consent process. Afterward, participants were informed that they were participating in a study involving the relationship between memory and other cognitive abilities. Participants in the before-encoding condition were told that they would be playing a word-generation game with the computer, but that they must first recount a memory from a prompt. Depending on power condition, participants then received one of three writing prompts (adapted from Gruenfed et al., 2008). In the high-power condition, participants read the following instructions: Please recall a particular incident in which you had power over another individual or individuals. By power, we mean a situation in which you controlled the ability of another person or persons to get something they wanted, or were in a position to evaluate those individuals. Please describe this situation in which you had power—what happened, how you felt, etc. In the medium-power condition, participants read the following instructions: Please recall a particular incident in which you were equal partners with someone. By equal partners, we mean a situation in which you and your partner did not report directly to one another, nor did one of you have disproportionate power or control over the other. Please describe this situation in which you were equal partners—what happened, how you felt, etc. Finally, in the low-power condition, participants read the following instructions: Please recall a particular incident in which someone else had power over you. By power, we mean a situation in which someone had control over your ability to get something you wanted, or was in a position to evaluate you. Please describe this situation in which you did not have power—what happened, how you felt, etc. After having three-minutes to describe the incident/relationship, participants were asked to play four rounds of a word-generation game with the computer. This game is quite similar to tasks used in other IP research (e.g., Brown & Murphy, 1989; Macrae et al., 1999). Each round consisted of a set of letter prompts (“BE,” “FO,” “MA”, “TE”) that the computer and participant were to use to create words (e.g., “bed,” “before” in the “BE” category). Each round began with the computer providing an example of the orthographic category, and then the participant was instructed to provide a unique answer (one not already mentioned by the computer or the self). This continued until 6 “turns” had been taken. Once the first orthographic category was done, the game began anew, but this time with a new category. In total, four categories were used, and

thus, at the end of the game, 48 answers were provided (12 in each category), 24 each provided by the computer and participant. The computer randomly drew its answers from a predetermined list, without replacement, and was programmed to take 5s to respond. Participants were reminded throughout not to duplicate responses. Following the word-generation game, participants took part in a roughly three-minute filler task. In this task, participants were asked to read and evaluate a brief, fabricated news article (this was done to clear short-term memory). After the filler task, participants were provided a response sheet on which they were to recall the words they themselves provided during the word-generation game (hereafter called the recall-own task, as in previous work, e.g., Brown & Murphy, 1989, Macrae et al., 1999). To explore participants’ retrieval process and experiences, I also asked participants to make a remember-know-guess (RKG) decision about each of their written responses. Following instructions adapted from Gardiner, Java, and Richardson-Klavehn (1996), participants indicated if they remembered (R) providing the word during the generation task, knew (K) they provided the word, or were guessing (G) about the word. The recall-own response sheet was divided into four columns (see Appendix for a copy of the recall-own sheet used in this experiment). Each column was labeled with one of the orthographic categories from the word-generation game and had six spaces for recall responses beneath. Next to each response space, the letters R, K, and G appeared (for remember, know, guess, respectively). Participants were instructed to, within each category, recall only the words they provided during the generation game. They were further encouraged to not leave any responses blank, however they were not to provide inaccurate responses knowingly. Additionally, they were provided with descriptions of what remembering, knowing, and guessing entailed, and were to circle the corresponding letter (R, K, or G) next to each word. After participants completed the recall-own task, they reported their gender, race, class standing, and age. Additionally, they were asked about their naïve theories concerning the study’s purpose and any perceived relationship between the various tasks. Once this information was collected, the experiment ended. Participants were then thanked for the participation, debriefed, and dismissed. For participants in the after-encoding condition, the experiment unfolded in an identical fashion, except that the order of the power prime and filler tasks was reversed. That is, participants: read and evaluated the fabricated news article (the filler task), played the word- generation game, wrote about a high, medium or low power situation, completed the recall-own task, and finally completed the brief demographics questionnaire. It is important to note that the delay between the end of the word-generation game and the start of the recall-own task was three minutes in both the before- and after-encoding conditions. Thus, any delay-induced source- monitoring or general-memory failures were equated across all conditions.

Results Dependent measures and scoring . The errors participants made in each of the experimental phases will be used as the units of analysis. For each participant, raw and proportion scores were calculated for each of the four error types described below. Raw scores were simply the number of times each type of error occurred. Proportion scores, however, were calculated by dividing the raw score by the total number of appropriate responses provided by the participant across all four word categories (more details will be provided about this below).

There were no differences in outcome patterns between analyses that used the raw and proportional scores, so all results will be discussed in terms of the proportional values. Participants could have made two different types of errors while playing the game. First, they may have repeated an answer they themselves had provided earlier in the game (hereafter termed self generation errors). Second, they may have repeated an answer provided earlier by the computer partner in the game (hereafter termed other generation errors). Generation proportion scores were calculated by taking the total number of (self or other) errors and dividing by the number of appropriate category responses made during the generation task. Across the four conditions, participants were to have provided 24 unique words, six within each category. However, if a participant provided one word that was not category-appropriate (e.g., “fail” in the FO category) then his/her generation task total would be 23. Thus, to calculate the proportion of generation errors (partner or self) for this participant, I tallied the number of such errors and divided by 23. 2 Participants may have also made errors during the recall-own task. Specifically, they may have recalled a computer’s answer as one’s own (hereafter termed IP errors), or they may have “recalled” a word that fit the category (e.g., words that began with “BE”) but had never been provided by anyone during the game (hereafter termed intrusion errors). It is important to note that only inadvertent plagiarism (IP) errors in the recall-own task are errors in source monitoring; intrusions are simply memory errors. The proportion of IP and intrusion errors were calculated by dividing the raw number of errors by the total number of non-repeated, category-appropriate responses provided during the recall-own task. To make this more concrete, if a participant wrote down 20 total responses on the recall-own sheet, but one response appeared twice (e.g., the participant recalled “bed” twice) and one response was category inappropriate (e.g., the participant listed “dog,” which did not fit any of the categories), I considered the total responses to be 18. To calculate the proportion of IP and intrusion errors for this participant, I would have tallied the number of such errors and divided by 18. 3 The raw number of IP was tallied by examining the number of times a participant recalled a computer-generated word that the participant also did not generate during the game. That is, if a participant committed an other generation error (e.g., generated “bed” after the computer had already done so), and then recalled that same word on the recall-own sheet, it did not count as an IP error because the participant had, despite it being a generation error, still provided it during the generation task. Additionally, if a participant recalled the same computer- generated word twice on the recall-own sheet, the double response was considered a duplicate and was only counted as one instance of IP, with the recall total adjusted accordingly (though this only happened once across all participants).

2 Twelve participants provided a total of 21 category-inappropriate responses during the generation task. If I include these in the calculation of the self and other generation proportion errors (i.e., divide each raw score by 24), it does not change the pattern of the data.

3 Ten participants had a total of 15 responses that were either recall-own repetitions or were category-inappropriate recall-own responses. The pattern of results described in the main text does not differ when I instead create IP proportion scores by taking the raw number of IPs divided by the total number of responses provided (i.e., including those recall responses that are repeated or category inappropriate).

Analysis of errors. I first examined self and other generation errors which, again, occurred when the participant repeated him/herself or the computer during the course of the word-generation game. During the game, a participant, at most, needed only to remember up to 11 words within a relatively short time frame, which is not overly difficult. Indeed, previous work using similar paradigms has shown that participants are generally fairly accurate at avoiding duplicate responses during the generation phase (e.g., Macrae et al., 1999). Thus, I expected few of both types of generation errors, and did not expect them to vary by power level or timing. I conducted a 3 (power level: high, medium, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA for both generation error types separately. As anticipated, there was no main effect of power level, or power timing, nor an interaction between the two (all ps>.436), and the rates of both types of generation errors were quite low (see Table 1). I next examined intrusion errors. Again, these occurred when a participant “recalled” a word from the generation phase that was not provided by either the participant or the computer. I subjected the proportion of intrusion errors to a 3 (power level: high, medium, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA. As anticipated, power level did not have an effect on the rate of intrusions, nor did it interact with power timing, ps>.682 (see Table 2). However, there was an unexpected main effect of power timing, such that participants that received the power manipulation before encoding ( M=.177) had fewer intrusions than those who received the manipulation after encoding ( M=.250), F(1,100)=7.057, p=.009. To my knowledge, there is no theoretical basis for this effect. The main focus of this work concerns the proportion of inadvertent plagiarism errors during recall, when a participant claimed a computer answer as a self answer. I subjected the proportion of IP errors to a 3 (power level: high, medium, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA. Though not significant, there tended to be more IP errors when the power manipulation was introduced before encoding ( M=.127) than after ( M=.104), F(1,100)=1.792, p=.184. Of more theoretical interest, and consistent with my prediction that differences in power would impact rates of plagiarism, there was a near-marginal main effect of power level, F(2,100)=2.021, p=.138. I used two different analytic strategies to further examine this outcome. First, I conducted traditional post-hoc analyses to examine which means, if any, differed from one another. These analyses showed that high-power participants (M=.138) committed a greater proportion of IP errors than did low-power participants ( M=.094), LSD p=.042. Neither high- nor low-power participants differed in IP errors from medium-power participants ( M=.115), though this mean fell in the middle descriptively. I next conducted correlational analyses. Though the low, medium, and high power conditions could be considered different levels of a categorical variable, they are also ordered along a continuum and thus could be construed as a continuous or ordinal variable. A correlation between power [coded as: low (- 1), medium (0), high (1)] and IP errors was significant, suggesting that there is a linear relation between the two, r(104)=.198, p=.042. A Spearman rank-order correlation between power and IP yielded a similar outcome, r(104)=.202, p=.037. Thus, with increasing power, there was increasing rates of IP. Earlier I discussed the possibility that power might have an influence on IP only when introduced prior to encoding. I argued that high-power participants might not “bind” other sources to their contributions, as much as those lower in power. Therefore, when high power was introduced prior to source-information encoding, it should increase IP errors. Further, I argued that if inadequate binding alone accounts for high-power participants’ tendencies to plagiarize,

then there should be a power difference in the before encoding condition but no such difference in the after condition. This hypothesis, if true, would have produced a significant interaction between power condition and power timing. However, this interaction was not significant, F(2,100)=.956, p=.388. Nevertheless, though not significant, it descriptively appears that the power manipulation had greater influence when presented prior to versus after encoding (see Figure 1). In fact, in the before-encoding condition, the power main effect is close to conventional levels of statistical significance, F(2,52)=2.782, p=.071, and there is a significant correlation between power and IP, r(53)=.311, p=.02. However, in the after-encoding condition, the power effect is clearly nonexistent ( p=.886), with no correlation between power and IP, r(49)=.067, p=.643. Though not perfectly conclusive, these findings suggest that power may have an influence on IP only if introduced before encoding, which suggests that inadequate source binding may be the causal mechanism. I hypothesized that as power increases, so too should rates of IP. Examining three levels of power (low, medium, high) is a sensible way to examine this hypothesis. However, the psychological distance in experienced power is relatively small between the medium condition and the other two. I wondered if examining power experiences just at the extreme ends of the spectrum (low versus high) might better reveal my hypothesized results. Thus, in a supplemental analysis, I analyzed just the high and low power conditions. Specifically, I conducted a 2 (power level: high, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA on the IP proportion scores. The analysis revealed a main effect of power level, such that the high-power participants plagiarized more than the low-power participants, F (1,65)=4.345, p=.041. There was not an independent main effect of power timing ( p=.311), nor did it interact with power level, F(1,65)=2.032, p=.159, though the descriptive pattern of the interaction was suggestive. Specifically, it showed that high-power participants plagiarized more than low-power participants in the before-encoding condition, F(1,34)=5.836, p=.021, whereas, there was no power difference in the after-encoding condition, F(1,31)=.235, p=.631. These findings suggest, then, that feeling powerful before encoding a “partner’s” contributions leads to much higher rates of IP than does feeling powerful after encoding or feeling powerless at any juncture. Indeed, a contrast comparing the high power/encoding condition to the other three confirms that this is the case, t(65)=2.66, p=.01. Thus again, the results from these supplemental analyses are consistent with the hypothesis that high power increases rates of IP and that such an effect is likely due entirely to inadequate source binding. Analysis of the Remember-Know-Guess data. For purely exploratory purposes, I asked participants to report their remember-know-guess experiences for each response they provided on the recall-own sheet. I did not have any a priori hypotheses for how power might influence such outcomes, but felt that these data might prove interesting and suggest possible future avenues of work in this area. For each participant, proportion scores were created, one each representing the three types of recall responses crossed with the RKG experiences. That is, I counted how many IP errors were remembered, how many were known, and how many were guessed. A similar tally was obtained for intrusions, and hits (correctly recalled self-generated words). These tallies were divided by the total number of non-repeated, category-appropriate recall responses provided. This resulted in nine unique variables (e.g., proportion of IP responses that they “remembered,” proportion of IP responses that they “knew,” etc.). To examine the effect, if any, power condition

and timing had on these responses, I ran a 3 (response type: IP, intrusion, hit) × 3 (retrieval experience: R, K, G) × 3 (power level) × 2 (power timing) mixed-model analysis, with between- subjects on the latter two factors. Though there were five significant effects, none of them were a main effect or an interaction involving power level (see Table 3 for the pattern of means).4 Thus, it appears that while power does, in some instances, influence perceived ownership of information, it does not affect the recall experience. That is, power differentials do not make individuals more or less likely to, for example, have an experience of knowing versus guessing.

Discussion The findings of Experiment 1 suggest that those who recall high positions of power may accidentally claim others’ ideas as their own if they experience that sense of power before hearing others’ contributions. Though power, at least at extreme levels, has an effect on IP errors, it does not similarly influence the other types of errors present within this design. Specifically, participants were no more or less likely to make the other memory errors (self/other generation errors, intrusions) as a result of high power exposure. Thus, it appears that high power only influences those errors that are related to source monitoring. These resultant source monitoring errors were instantiated only when power was introduced prior to information encoding. Thus, it appears that when an instance of high power is recalled, participants were less likely to “bind” information to the appropriate source (e.g.,

4 Below are the significant results from the 3 (response type: IP, intrusion, hit) × 3 (retrieval experience: R, K, G) × 3 (power level) × 2 (power timing) mixed-model analysis:

a) A main effect of response type, F(2,200)=329.389, p<.001, indicating that participants had fewer IP responses ( M=.115) than intrusions ( M=.211, p<.001) and fewer intrusions than hits ( M=.665, p<.001).

b) A main effect of recall experience, F(2,200)=6.259, p=.002, indicating that participants were more likely to “know” ( M=.399) they provided a given response rather than “remember” ( M=.312, p=.035) or “guess” (M=.278, p<.001).

c) An interaction between response type and power timing, F(2,200)=4.248, p=.016. There was a greater proportion of intrusion responses when the power manipulation was introduced after encoding ( M=.250) than before ( M=.174), p=.007. Conversely, when the power manipulation was introduced before encoding there was a marginally greater proportion of both IP responses ( Mbefore =.126 v. Mafter =.103, p=.178) and hits (Mbefore =.689 v. Mafter =.638, p=.119) than after encoding.

d) An interaction between recall experience and power timing, F(2,200)=3.422, p=.035. Participants were more likely to indicate they remembered providing a word if the power manipulation was introduced before encoding ( M=.364) than if after ( M=.257), p=.021. The opposite pattern was observed for words they guessed about ( Mbefore =.244, Mafter =.315), p=.028. There was not a difference in the rate of “knowing” a word ( Mbefore =.383, Mafter =.418), p=.457.

e) An interaction between response type and recall experience, F(4,400)=70.477, p<.001. For IP responses, “guessing” ( M=.055) was more frequent than was “remembering” ( M=.037; p=.061), which was more frequent than “knowing” ( M=.023; p=.08). For intrusions, there was not a difference in rates of remember (M=.023) or know ( M=.022) responses, p=.895. However, participants were more likely to “guess” at the word ( M=.166) than “know” ( p<.001) or “remember” (p<.001) they provided it. Finally, for hits (accurate recalls), participants were more likely to “know” that they provided a given word ( M=.355) than “remember” ( M=.253, p=.019) or “guess” ( M=.057, p<.001). They were also more likely to “remember” than “guess,” p<.001.

Macrae et al., 1999), thus increasing later rates of IP. This finding is consistent with the literature showing that high-power individuals are less likely to attend to the unique qualities/contributions of others (e.g., Fiske, 1993; Goodwin et al., 2000). As such, power only has an influence on plagiarism rates when there is an opportunity for it to influence source binding as well. When power was introduced after encoding, source “binding” had already occurred and thus could not be influenced. Importantly, these results do not support the notion that high power participants would plagiarize more even if source binding has already occurred (i.e., in the after encoding condition) due to a lack of motivation or effort to recall the source of the contribution. Thus, it is not that high power people simply disregard correct source information that they have available.

Experiment 2

Experiment 1 provided evidence to suggest that when power is introduced prior to the encoding of source information, high-power participants are more likely to inadvertently plagiarize others than are low-power participants. The power manipulation in Experiment 1 asked participants to recall an incident in their past in which they had more (less, equal) power in relation to someone else. Though that manipulation seemed like a reasonable way to begin to investigate the relationship between power and cryptomnesia, I felt it important to also use an additional manipulation, one that puts participants in a current situation in which their partner is more/less powerful than they are. To do this, Experiment 2 employed an outcome dependency manipulation to vary power levels. The manipulation in Experiment 2 is decidedly more dynamic than the one employed in Experiment 1. Specifically, participants will believe that they will be completing the generation task with a real partner, with varying levels of power between the two. In the high power condition, the participant will believe he or she controls whether the partner gets to complete a “fun” (desirable) subsequent task versus a “boring” (undesirable) subsequent task. In the low power condition, the participant will believe that his or her partner will be making the task assignments. My hypothesis, based on my original theorizing and the results of Experiment 1, is that participants in the high power condition will engage in more IP than those in the low power condition, but only when power is instantiated before encoding. If the results of this experiment are as anticipated, they will represent an interesting and meaningful extension of Experiment 1’s findings for a number of reasons. First, such an outcome would show that even if power is not explicitly mentioned (as it was in Experiment 1), it can have the same impact on IP. Second, such an outcome would confirm that an experience of power/powerlessness in a more ecologically-valid setting can trigger differential rates of IP. That is, the methodological changes in this study make it more closely mimic power asymmetries we experience in daily life.

Method Participants and design. Participants were 78 (44 female) Miami University students enrolled in PSY111 who received partial course credit for participation. One participant was removed for not following directions. The study was a 2 (power level: high, low) × 2 (power timing: before encoding, after encoding) between-subject design. To focus my examination on the extreme ends of the power spectrum, the medium condition employed in Experiment 1was dropped from this experiment.

Procedure. Participants arrived at the lab in groups of 1 – 6 and were greeted by a female experimenter. Each participant was seated in a private cubicle and completed the informed consent process. Afterward, participants were informed that they were participating in a study involving cognitive abilities and that they would be playing a word-generation game with a partner who is currently in another lab within the building. In actuality, there was no “real” partner, and the participants played against the computer, as described in Experiment 1. To bolster the credibility of the assertion that the participants would be playing the game with another person, the experimenter made reference to the participants’ partners currently in another lab within the building and told them, just prior to the word-generation task, that she had just checked in with the other lab, via computer, and it looked like everyone’s partners were ready to begin. The subsequent procedures for this experiment follow those used in Experiment 1, with the following exceptions. Instead of recalling a past power-related event, participants were told that the experimental session would consist of two blocks of studies. The first block, which they were currently completing, was the same for everyone, including their partner. The second block, they were told, would consist of one of two possible tasks. They were told that, in order to save time, the two remaining tasks would be split between the partners. On the desk in each participant’s cubicle room was a sheet of paper that described the tasks and how they would be divided. Participants were randomly assigned to either the low or high power conditions, which determined the task assignment instructions they received. Namely, low-power participants learned that their partner would be deciding who completed which task, whereas high-power participants learned that they themselves would be making the task-assignment decision. The task descriptions were adapted from Bargh, Gollwitzer, Lee-Chai, Barndollar, and Trötschel (2001; Exp. 5). These authors had two tasks, which pretested at different levels of enjoyableness: a scrabble word-forming task (low in enjoyableness) and a cartoon-rating task (high in enjoyableness). Thus, the power in this manipulation comes from the participant having or not having control over a valued outcome. Specifically, if the participant gets to decide who does the fun task and who does the boring task, this should make him/her feel powerful. On the other hand, if the participant is going to be assigned a task by another, he/she should feel powerless. For participants in the before encoding condition, they learned about the desirable and undesirable tasks and the fact that they (or their partner) would get to make the task assignments before playing the game (this took about 3 minutes of time to read). However, neither they, nor their partner, made the task assignments at that time. For participants in the after encoding condition, they learned about the two tasks and their role (or their partner’s) in handing out the task assignments after playing the word-generation game, but before completing the recall-own sheet, and also did not actually make the task assignment decision at that time. Importantly, as in Experiment 1, the delay between the word-generation game and the recall-own task was three minutes in both the before- and after-encoding conditions. Thus, similar to Experiment 1, those in the before encoding condition first got the power information, then played the word- generation game, then completed the three-minute filler task (used in Experiment 1), and then completed the recall-own task. Those in the after encoding condition did these same tasks, but the filler task and the power manipulation task were reversed. The same recall-own sheet used in Experiment 1 was used for Experiment 2 (with references to “computer” changed to “partner”). Therefore, participants again rendered R-K-G judgments. However, because these data yielded nothing of relevance regarding power in Experiment 1, they were not scored and will not be discussed further. After the recall-own task, participants were debriefed and made aware that

they were not playing with a partner, only a computer, and that there were no additional tasks to complete.

Results As in Experiment 1, I will be using the errors participants made during both the generation and recall portions of the experiment as the units of analysis. The proportional error values were calculated in the exact same way as described above. 5 I began by examining self and other generation errors, conducting a 2 (power level: high, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA for each generation error type separately. As expected, there were no main effects of power level or power timing, nor an interaction between the two (all ps >.265). As can be seen in Table 4, the rates for each of these errors were consistently low. I next examined the intrusion errors in a 2 (power level: high, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA. As in Experiment 1, there was not an effect of power level on intrusions, F(1,73)=.011, p=.917. Additionally, there was not an effect of power timing, F(1,73)=.312, p=.578. There was, however, a marginal interaction between the two, F(1,73)=2.653, p=.108. An examination of the means shows that in the before encoding condition, high power participants made more intrusion errors than those in the low power condition, but that the reverse was true in the after encoding condition. Neither of these simple- effect comparisons, however, was significant, ps >.227 (see Table 5). I next examined the dependent measure of primary interest, the rates of IP errors. These errors were subjected to a 2 (power level: high, low) × 2 (power timing: before encoding, after encoding) between-subject ANOVA. This analysis yielded no significant effects. Namely, there was no main effect of power timing, as the results indicate no difference between those that received the power manipulation before ( M=.113) versus after ( M=.099) encoding, F(1,73)=.454, p=.503. There was also no main effect of power level, F(1,73)=1.588, p =.212. Further, the pattern of the means revealed a descriptive reversal of that predicted. Namely, it was the low power participants ( M=.120) that committed more IP errors than the high power participants (M=.093), though this difference was not significant. Of most importance, there was also no interaction between power level and timing, F(1,73)=.118, p=.733 (see Figure 2). The general tendency for low-power participants to engage in higher rates of IP than high-power participants was roughly equivalent in the before and after encoding conditions. The power manipulation in this experiment relied heavily on deception, in that participants needed to believe that they were indeed interacting with a partner that they had power over (or that had power over them). If participants were in doubt of this, then they would not have felt more/less powerful, which would yield null findings. Unprompted, nine participants indicated, either on the recall-own response sheet or during debriefing, that they did not believe they actually had a partner. If these participants are removed, I find a similar pattern of data as reported above. Specifically, participants in the low power condition ( M=.115) were still more likely to plagiarize than those in the high power condition ( M=.086), F(1,64)=1.599, p=.211, though obviously not significantly so. Moreover, there was still no significant interaction

5 The patterns of data reported in the main text do not change if the raw error values are used instead of the proportional scores, nor if the proportional recall errors (IP, intrusions) are created by using the total number of recall responses including repeated and category-inappropriate responses.

between power level and power timing, F(1,64)=.612, p=.437 (see Figure 3). Thus, both sets of analyses failed to replicate the significant (or marginally-significant) patterns observed in Experiment 1.

Discussion In contrast to Experiment 1, the results of Experiment 2 did not support the hypothesis that high power participants will inadvertently plagiarize more than low power participants, especially if power is instantiated prior to encoding. If anything, the data from Experiment 2 trended toward the opposite pattern. I suspect that a primary reason that I observed null findings on IP errors is because the power manipulation was not believable. Thus, I am hopeful that these findings represent a failure of methodology and not a failure of my theory and hypotheses. As stated above, nine participants explicitly reported skepticism as to the presence of a real-life partner. Unfortunately, there was not a specific, targeted suspicion-check question asking participants if they did, in fact, believe they were interacting with another human. Instead, I asked broad questions like, “What did you think this study was about?” The recall-own sheet I used for Experiment 2 was identical to the one used in Experiment 1. Because Experiment 1 involved less deception, the broad post-experimental questions were likely perfectly appropriate for Experiment 1. A more targeted suspicion question should have been added to Experiment 2, but, unfortunately, this did not happen. Anecdotally, some participants expressed concern that they were not completing the final task that they (their partner) chose, thus providing limited evidence that some participants did believe the cover story. However, there is no way to know what proportion of participants actually believed their partner was real. And, for those who did not believe a partner existed, they would not have experienced a feeling of power (or powerlessness), and thus there would be no opportunity for power to influence their rates of IP. There is one feature of the word-generation game that, in hindsight, may have made the presence of a partner seem unlikely: the speed and regularity with which the “partner” responded during the word-generation task. During the game, once a participant entered his or her word, the “partner’s” (computer’s) response appeared fairly quickly. This fast response may have led participants to question if they were actually dealing with a live partner (and at least one participant verbally indicated as such). Additionally, the instructions explicitly told participants not to repeat earlier words. In order to avoid repeat responses, one must obviously pay some attention to the words that had been previously presented and, if a response is fairly immediate, it seems unlikely that the “person” took the time to read the participants’ responses. Thus, the consistently fast response time was likely obvious to many participants. The word-generation game requirement that the computer/partner provide responses that do not duplicate a participant’s response is not something that MediaLab, the experimental software available in my lab, is capable of, and I lack the computer programming skills necessary to create a word-generation game of this sort from “scratch.” Thus, I sought help from a programmer to create this game. Should I attempt to repeat Experiment 2 in the future, hopefully the program could be altered to provide computer responses in a manner that more closely mimics what a human might do (i.e., respond more slowly and more irregularly).

General Discussion

Being caught plagiarizing another’s ideas can devastate a person’s professional or academic career, and educators try to teach students proper citation techniques and warn them of

the dire consequences that can ensue should they be careless with others’ intellectual property. The relatively small literature on inadvertent plagiarism, however, suggests a chilling possibility: that despite one’s best efforts and diligence, one may accidentally take credit for another’s idea. Many in this literature have argued (Johnson et al., 1993; see also Macrae et al., 1999) that faulty or improper source monitoring may be the culprit responsible for IP. That is, when one cannot easily differentiate whether the source of an idea is internal versus external or does not stop to carefully consider this internal/external distinction, source errors arise, leading to acts of IP. In this work, I sought to examine whether the psychological experience of power might increase the likelihood of this unfortunate problem. This hypothesis was based on findings that suggest that people in power often deal with other sources fairly superficially (e.g., Goodwin et al., 2000) and are often unmotivated to think carefully (Dépret & Fiske, 1999; Fiske & Dépret, 1996). Either of these processes or both working in combination, I argued, should give rise to greater rates of IP errors than would be produced by those with less power. Because many of the statistical results were marginal and because most of the conventionally-significant findings came from the supplemental analyses that focused on only the low and high power conditions, all of my conclusions must be interpreted with caution. With this in mind, the findings from Experiment 1 suggest that those who occupy high positions of power are more likely to accidentally claim others’ ideas as their own if they experience that sense of power before hearing others’ contributions. The fact that the timing of the power induction matters helps elucidate the precise mechanism responsible for power’s influence on IP. As outlined above, there may be two mechanisms by which power influences IP, source binding and motivation, and these processes are differentially “in play” depending on the timing of the power induction. At encoding, if one does not accurately “bind” together the information and its source, inadvertent plagiarism is likely. To explain, when a contribution comes to mind during the recall- own task, if it was originally stated by one’s partner, but this fact was not properly encoded, then the participant may believe that he or she is its true source. Such binding failures are more likely to happen with high power participants because they, in general, pay less detailed attention to others in their environment and deal with them in only a superficial manner (Chance, 1967; Dovidio et al., 1988; Goodwin et al., 2000). Importantly, if high power is leading to inadequate source binding, and if this is the sole reason for why high power people plagiarize, then a power differential should be observed in the before encoding condition only, as instantiating high (or low) power after an interaction cannot, by definition, harm the encoding of information. The second possible process that might give rise to high rates of IP occurs when people do not take the time and effort necessary to consider the source decision. Such a lack of motivation may be especially likely to occur for high-power people because they may see others and their responses as a way by which to reach their own goals (Keltner et al., 2003). Or it could simply be that those in power do not recognize, or even realize, that they need to think about source information. If this lack of motivation is operating during the recall-own task for high power people, they will engage in greater rates of IP than those low in power, and it would make no difference whether the power originally began before or after the interaction. Thus, if this lack of motivation is the sole reason for why power might increase rates of IP, then high power people should plagiarize more than low power people equally in both the before and after encoding conditions. Finally, if both lack of motivation and inadequate source binding occur and can influence plagiarism, I might expect an additive effect, such that when power is instantiated before

encoding, both processes are working together to increase IP to especially high levels. If instantiated after encoding, only a lack of motivation is operating to increase IP. Thus, high- power participants might plagiarize more than low power people in both the before and after encoding conditions, but the effect would be bigger in the before condition. Given the findings of Experiment 1, that high power participants inadvertently plagiarized more than low power participants in the before encoding condition only, this suggests that high power is causing high rates of IP via inadequate source binding. Of course, it is dangerous to conclude that power’s influence on IP has nothing to do with a lack of motivation to consider the source decision. After all, such a conclusion would be based solely on one null finding (in the after encoding condition). In follow-up work, it might be useful to try to manipulate motivation and observe how powerful people inadvertently plagiarize (or not) under such conditions. One potential method by which to manipulate motivation would be to pay participants for accurate (non-plagiarized) recall-own responses. That is, shortly before completing the recall-own sheet, some high power participants could be told that they will receive $1 for each correct, non-partner response they provide, whereas other high power participants could be offered no such incentive. If this manipulation has no effect on rates of IP, then I could more confidently rule out motivation’s role in causing high power participants’ greater rates of IP. Based on the findings of Experiment 1, it does seem likely that some level of inadequate source binding is causing high power participants to engage in IP. Given all of the applied implications of cryptomnesia work, especially in power contexts, it may be beneficial to determine how to reduce IP. As outlined above, high power individuals tend to overlook the unique qualities and contributions of those around them and, as such, pay them more superficial attention (e.g., Dovidio et al., 1988; Goodwin et al., 2000). Thus, if there is a way to increase the amount of systematic attention high power individuals pay to others, then it should be possible to decrease their rates of IP. Again, using a financial incentive could be useful. That is, if high power participants are offered a financial incentive to avoid plagiarism before the encoding task , this might help prevent their problematic responses. If high power participants know that their earning money will be contingent upon them not stealing their partner’s ideas, perhaps they will pay more careful attention to their partner’s responses during encoding, which should substantially bring down their IP errors. Another important avenue for future work should focus on whether high power actually increases IP, whether low power decreases IP, or both. To answer this question, one needs to conduct a study with a “true” control condition. Experiment 1 had a “medium” power condition, and rates of IP fell “in between” the high and low conditions, though it was not statistically different from either. In retrospect, it would have been better to include a condition that had no mention of power at all and to compare the high and low power conditions to that pure control. Also, as previously discussed, I would like to replicate the finding that high power increases rates of IP (when instantiated before encoding) using a more dynamic and ecologically- valid power induction. Experiment 2 attempted to do this, but, of course, only null findings emerged. As already discussed at length, I believe the failure of Experiment 2 is due primarily to participants not believing that they had a human partner. If a substantial proportion of the participants did not believe they had a partner, then, by extension, they likely did not believe they truly had power over this person (or were powerless in comparison to this person). Methodological tweaks, such as making the computer respond more slowly and irregularly or

having the participant meet his/her “partner” (a confederate) in the lab, could bolster the believability of the cover story and make success of the manipulation more likely. More globally, I hope these studies will be the first in a long line to examine the impact of different social-psychological variables on rates of IP. As mentioned earlier, this literature is extremely small, and only Macrae and colleagues (1999) have uncovered any social- psychological factors that influence this phenomenon. In addition to similarity (which they investigated) and power (which I have investigated), many other social factors could contribute to IP. For example, might partner attractiveness play a role? Research has shown that we tend to divert more of our attention to those that we consider attractive (e.g., Maner, Gailliot, Rouby, & Miller, 2007), and this could influence our source monitoring. Specifically, a highly attractive source may encourage greater source monitoring than would a less attractive source, resulting in fewer IP errors. If such an effect were to occur it could potentially even be moderated by participant sex and sociosexual status. Maner and colleagues (2007) found that those with an unrestricted sociosexual status (i.e., who were single) were more likely to devote attention to attractive opposite-sex others, whereas those with a restricted sociosexual status (i.e., who were in a relationship) were more likely to devote attention to same-sex attractive others, to facilitate mate-searching and mate-guarding, respectively. Thus, we should be better able to source monitor those attractive people who elicit our attention (for whatever reason), leading to less plagiarism of their responses. Overall, the results of the current work may speak to how existing power differentials are maintained. Imagine a situation in which awards are given for ideas generated. Such situations are likely frequent in the business world, when innovative ideas garner people raises and promotions. If those in higher positions of power are more likely to plagiarize information, they may inadvertently claim an idea as their own to the detriment of the actual source. That is, if these stolen ideas were highly regarded, this may garner additional power/benefits for the plagiarizer and leave the original source in his/her current position. Thus, there may be little room for vertical movement up the ladder for those with relatively little power. Finally, it is important to note that this work (and the follow-up work it may inspire) could have important implications for education practitioners and education researchers. Plagiarism likely gets the most attention in academic contexts. For obvious reasons, educators have an interest in preventing students from engaging in plagiarism – deliberate or otherwise. This research has the potential to help scholars learn more about the processes that give rise to accidental plagiarism, which eventually could be used as a basis for crafting recommendations that are passed to students to help them avoid such costly errors. Thus, this work could forge interdisciplinary ties between psychology and education in important and meaningful ways.

References

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Appendix

Earlier in the experiment today, we asked you to play a word-generation game with the computer. In each version of the game, you generated 6 examples in the given category. We want you to try to recall the answers you provided during the game. If possible, please write down the 6 answers you provided in each category, that is, please do not leave any blanks below. However, please do not provide words that you know you did not generate during the word- generation game.

In addition, we would like you to indicate if you remember (R) providing the word, know ( K) you provided the word, or are guessing ( G) about the word. Please circle the letter next to each that best describes your recall of that word. Use the outline below to aid in making your decision:

• R – Remember: Recalling this word brought back to mind something you experienced during the word- generation game, and that this might include an image or association formed then, something of personal significance the word had reminded you of at that time, or something about the physical nature of its presentation. • K – Know: You know for a fact that this word occurred during the word-generation game, because the word is familiar, but you do not recollect its occurrence. • G – Guess: This word elicits neither the experience of remembering nor of knowing, it is a word that you might have provided during the word-generation game and that a guess response is appropriate.

words starting with “be” words starting with “fo” words starting with “ma” Words starting with “te”

1. ______R ______R ______R ______R K K K K G G G G

2. ______R ______R ______R ______R K K K K G G G G

3. ______R ______R ______R ______R K K K K G G G G

4. ______R ______R ______R ______R K K K K G G G G

5. ______R ______R ______R ______R K K K K G G G G

6. ______R ______R ______R ______R K K K K G G G G

(Continue to back side of page when done )

Please answer the following demographic questions about yourself:

1. I am (circle one): Male Female

2. My racial identify is (circle one):

American Indian Asian/Pacific Black, not of White, not of Islander Hispanic origin Hispanic origin

Hispanic Other (specify): ______

3. My class standing is (circle one):

Freshman Sophomore Junior Senior

4. I am ______years old

5. What do you think this study was about?

6. Do you think there was a relationship between any of today’s tasks? If so, what was it?

Table 1.

Self Errors Power Level

Power Timing High Medium Low Marginal Means

Before Encoding .009 .009 .009 .009

After Encoding .005 .010 .005 .007

Marginal Means .007 .009 .007

Other Errors Power Level

Power Timing High Medium Low Marginal Means

Before Encoding .028 .024 .023 .025

After Encoding .039 .031 .021 .030

Marginal Means .034 .028 .022

Table 2.

Power Level

Power Timing High Medium Low Marginal Means

Before Encoding .151 .188 .191 .177

After Encoding .248 .269 .233 .250

Marginal Means .199 .228 .212

Table 3.

IP Power Level

Power Timing High Medium Low

Before Encoding Remember .069 .038 .035 Know .030 .037 .010 Guess .062 .054 .044 After Encoding Remember .027 .037 .012 Know .017 .021 .021 Guess .071 .043 .060

Intrusions Power Level

Power Timing High Medium Low

Before Encoding Remember .038 .018 .012 Know .010 .015 .017 Guess .104 .155 .155 After Encoding Remember .025 .019 .027 Know .015 .040 .036 Guess .205 .208 .173

Hits Power Level

Power Timing High Medium Low

Before Encoding Remember .293 .334 .255 Know .353 .275 .404 Guess .033 .072 .051 After Encoding Remember .243 .161 .222 Know .342 .398 .363 Guess .052 .066 .067

Table 4.

Self Errors Power Level

Power Timing High Low Marginal Means

Before Encoding .013 .011 .012

After Encoding .007 .008 .007

Marginal Means .010 .010

Other Errors Power Level

Power Timing High Low Marginal Means

Before Encoding .024 .018 .021

After Encoding .035 .025 .030

Marginal Means .030 .021

Table 5.

Power Level

Power Timing High Low Marginal Means

Before Encoding .196 .146 .171

After Encoding .165 .209 .187

Marginal Means .180 .177

Figure 1.

0.18 0.16 0.14 0.12 low 0.1 medium 0.08 high 0.06 0.04

Inadvertent Plagiarism Inadvertent 0.02 0 before encoding after encoding Power Timing

Figure 2.

0.14

0.12

0.1

0.08 low 0.06 high

0.04

Inadvertent Plagiarism Inadvertent 0.02

0 before encoding after encoding Power Timing

Figure 3.

0.14

0.12

0.1

0.08 low 0.06 high

0.04

Inadvertent Plagiarism Inadvertent 0.02

0 before encoding after encoding Power Timing