Visual Working Memory: Capacity, Resolution, and Expertise

[First published on Nathen’s Miraculous Escape, July 20, 2009.]

Running Head: VISUAL WORKING MEMORY

Visual Working Memory: Capacity, Resolution, and Expertise

Nathen B. Lester

For PSY 435, Dr. Awh

University of Oregon

June 9, 2008

Visual Working Memory: Capacity, Resolution, and Expertise

Ideas in psychology change and develop in much the same way that they do in a conversation, a conversation taking place over years, primarily in the form of detailed written accounts of hypotheses, experiments, and results. It may be slow and technical, but it has the same form: Assertions are made, evidence is presented, mistakes are pointed out, and new assertions are made. Incrementally, the amount of knowledge is increased.

One such conversation that is ongoing in the scientific literature is about the capacity of visual working memory and how it may be affected by the perceptual expertise of the viewer.

Because working memory capacity is correlated with scholastic ability, attentional control, and scores on intelligence tests (Cowan, Elliot, Saults, Morey, Mattox, Hismjatullina, &Conway, 2005), it is a topic of considerable interest among researchers in cognitive psychology. The following sections describe three articles which are examples of an exchange between researchers on this topic which gives rise to new knowledge as well as raising new questions.

The Capacity of Visual Working Memory for Features and Conjunctions

In their article of 1997, Luck and Vogel argued for a visual working memory capacity of approximately four objects, regardless of how complex those objects are. They found mounting evidence for this in a series of experiments using Phillips’ (1974) change-detection paradigm, where subjects are shown an initial array of objects, a pause, and then a test array, with the task of indicating whether the two arrays were identical or different.  They conducted several experiments using arrays of visual objects which varied in their number and types of features, including a single color only, two colors for each object, object orientation only, color and orientation together, and finally objects which varied in their color, orientation, size, and the presence or absence of a gap. In all conditions of all experiments, subjects could accurately detect changes in about four of the objects in an array. This is strong evidence for an object-based working memory capacity and against a feature-based working memory capacity: Four objects were consistently remembered, whether those objects’ combined features equaled four, eight, or even 16 features.

Several other variations were used to rule out possible alternate explanations. To test for the possibility that their verbal working memories were aiding in the task, subjects were given a verbal load of two digits to remember, with no effect on their performance. To rule out the possibility that capacity estimates were being limited by the very brief presentation of the initial array, that presentation was increased from 100 ms to 500 ms, with no change in the results. To address the fact that more decisions had to be made when viewing larger test arrays, which could lead to more errors, another condition had subjects indicate whether one randomly chosen object had changed. This also did not affect the results. Finally, the condition in which each object had two colors was run to test the possibility that there are separate working memory systems for each kind of feature. Subjects in this condition could remember about four objects whether that meant remembering four colors or eight colors, evidence against a feature-based working memory system for color distinct from the system that remembers the other types of features.

A Visual Short-Term Memory Advantage for Faces

Curby and Gauthier’s 2007 article was an attempt to show the effects of holistic processing on visual working memory capacity, using a variation of the change-detection paradigm. Because of the greater efficiency of holistic processing, they reasoned, objects like upright faces, with which subjects have a lot of expertise, will be stored more efficiently in working memory. They hypothesized that this should result in a larger working memory capacity for faces than for other complex objects. Their experiments resulted in three basic findings: (a) At 500 ms of encoding time, subjects were less accurate in detecting changes between faces than they were in detecting changes between cars or watches. (b) At 2500 ms encoding time, subjects’ accuracy was equivalent for all categories. (c) At 4000 ms encoding time, subjects were more accurate with the faces than they were with the other categories of objects.

Curby and Gauthier’s (2007) explanation of these results was that for complex objects, perceptual encoding processes cause a bottleneck for creating representations in visual working memory. At the shortest encoding time, this results in fewer objects in memory from an array of faces than from arrays of less complex objects such as cars or watches. At the 2500 ms encoding time, the benefits of efficient, holistic processing brought the number of faces encoded up to the number of other objects. By 4000 ms of encoding time, those benefits allowed more faces to be stored in visual working memory than any other kind of object tested. In other words, given enough time, the benefits of the more holistic processing of faces outweighs their disadvantage of being more complex. Finally, based on this, they reasoned that the limits on the storage of complex objects in working memory hypothesized by Alvarez and Cavanagh (2004) are ameliorated to some degree by this efficient processing of faces.

Perceptual Expertise Enhances the Resolution but Not the Number of Representations in Working Memory

Scolari, Vogel, and Awh’s 2008 article was largely a correction and clarification of the meaning of Curby and Gauthier’s (2007) results: The benefit of expertise is not in the number but in the resolution of objects in working memory. The difference in subjects’ ability to detect changes in a face out of an array of faces compared to changes in, for example, a car out of an array of cars, was actually a measurement of comparison errors made between the memories formed and the test display, not the number of objects held in working memory. That is, when Curby and Gauthier (2007) thought they were measuring the quantity of objects in working memory, they were actually measuring their quality.

Scolari et al. (2008) managed to show this in one experiment using four categories of objects: faces, inverted faces, shaded cubes, and colored ovals. Within-category changes between the initial display and the test display replicated Curby and Gauthier’s (2007) results. In other words, subjects were more likely to detect a change from one upright face to another, as compared to a change from one cube to another or one inverted face to another, possibly reflecting the benefits of holistic processing for faces. Changes across categories, however, which eliminated the possibility of comparison errors, replicated Luck and Vogel’s (1997) results. In other words, when the changes were big, a face changing into a cube, for example, working memory capacity estimates were at about four objects, regardless of the complexity of those objects.

Scolari et al. (2008) also found that individual differences in subjects’ performance in the cross-category change detection tasks were correlated to their performance in their simple color-change detection task. This suggests that performance on these tasks produces a more pure estimate of working memory capacity than does performance on within-category tasks. Additionally, the cross-category individual differences were not correlated to the within-category individual differences, indicating that being able to hold a certain number of objects in working memory and being able to store details about those objects are distinct abilities, drawing on different resources.

Two Additional Voices

Two other articles are worth briefly describing to flesh out this conversation. The first of these is Alvarez and Cavanagh’s 2004, “The capacity of visual short-term memory is set both by visual information load and by number of objects.” This article was in part a reply to Luck and Vogel (1997) and set the stage for Curby and Gauthier’s error: Alvarez and Cavanagh measured what they thought was the complexity of the objects they used in their change-detection tasks and found that visual working memory capacity was limited by the complexity, and not just the number, of the objects therein.

The problem was that their operational definition of “complexity,” which was based on visual search rate, was confounded with similarity. That is, Alvarez and Cavanagh (2004) judged categories of objects more complex because they were more difficult to tell apart. This was pointed out by Awh, Barton, and Vogel (2007) in “Visual working memory represents a fixed number of items regardless of complexity.” Setting the stage for Scolari et al. (2008), Awh et al. (2007) showed that it was actually comparison errors, caused by object similarity, and notobject complexity that were producing the lower estimates for visual working memory capacity.

Discussion

Useful conversations rely on careful logic, clearly defined terms, and up to date information. In one way, the exchange here can be seen as corrective of errors in these areas.

Luck and Vogel (1997) used sound and thorough reasoning in combination with a series of very straightforward experiments to present evidence for an object-based visual working memory capacity of about four items, and, simultaneously, evidence against the idea that visual working memory is limited by the number of features each object has. Alvarez and Cavanagh (2004) presented what they thought was evidence for the complexity of objects being an additional limit to capacity, but Awh et al. (2007) showed that apparent limit to be a resource artifact from the difficulty of distinguishing highly similar items from each other. Almost certainly unaware of Awh and colleagues’ work, Curby and Gauthier (2007) set out to refine the work of Alvarez and Cavanagh (2004), stating that the complexity of objects may limit capacity, but expertise can overcome that limit to some degree. Then Scolari et al. (2008) pointed out that Curby and Gauthier (2007), relying on Alvarez and Cavanagh’s reasoning, had made the same error: Their results did not mean what they had thought. When comparison errors are eliminated, it is obvious that the number of objects stored in working memory is not affected by those objects’ complexity.

While in some ways side-tracks based on faulty reasoning, these works of Alvarez, and Cavanagh (2004), and Curby and Gauthier (2007), have also been useful in extending our knowledge. What we mean by the word “capacity,” for example, has been refined. “Capacity” has been used in a variety of ways, especially in Curby and Gauthier (2007), who used it to mean either the total number of “slots” available in working memory, the number of slots that happened to have been filled in a certain experiment, an amount of total information, and a kind of rate-based encoding capacity, in the vein of “objects encoded per second.” It is now clear to those with up-to-date information, that when discussing visual working memory, “capacity” should refer to the number of slots available for visual objects.

It should also be clear that we currently have a model for visual working memory that has at least two factors: capacity for storing objects and the resolution of those objects. Further, the information-load bottleneck may be a real phenomenon, but it is not about the time it takes to store complex items; it appears to be about the time it takes to build representations of sufficient resolution to avoid comparison errors. Furthermore, expertise, which may result in more holistic processing of visual stimuli, does seem to increase subjects’ ability to encode high-resolution memories, even if it does not increase the number of objects which can be stored.

Many good questions have been raised as well. Since search-rate based measurements have been ruled out, what are good operational definitions of “complexity” and “information load” in regard to visual objects? Is there a kind of “resolution capacity,” and how would it relate to expertise, given a good operational definition of complexity? How does this relate to the “consolidation time” estimates between 50 ms and 500 ms in Curby and Gauthier (2007, p. 627)? What is the role of expertise in the resolution of memories of objects other than faces? The most interesting question follows from the correlation of working memory capacity, intelligence scores and academic achievement (Cowan et al., 2005): Since individual differences in the resolution factor are not correlated with individual differences in the capacity factor (Scolari et al. 2008), what is the relationship between the resolution of visual working memory and intelligence?

References

Alvarez, G. A., & Cavanagh, P. (2004). The capacity of visual short-term memory is set both by visual information load and by number of objects. Psychological Science, 15, 106-111.

Awh, E., Barton, B., & Vogel, E. K. (2008). Visual working memory represents a fixed number of items regardless of complexity. Psychological Science, 18, 622-628.

Cowan, N., Elliot, E. M., Saults, J. S., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. A. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology 51, 42-100.

Curby, K. M., & Gauthier, I. (2007). A visual short-term memory advantage for faces.Psychonomic Bulletin & Review, 14, 620-628.

Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279-281.

Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory. Perceptual Psychophysiology, 16, 283-290.

Scolari, M., Vogel, E. V., & Awh, E. (2008). Perceptual expertise enhances the resolution but not the number of representations in working memory. Psychonomic Bulletin & Review, 15, 215-222.

A Summary of My Honors Thesis

I just posted the last two papers of my undergraduate career: my honors thesis, “Differentiating the Effects of Social and Personal Power,” and my research project for Psycholinguistics, “The Relationship between Clarity of Enunciation and Idea Density.” They are under ‘writing,’ which is under ‘out’ in my sidebar.

I don’t recommend reading them unless you are a researching these topics (in which case, I do recommend reading them). If you’re not used to scholarly writing, just read the abstracts–the first paragraphs. They tell you everything you need to know. It’s kind of funny that I just worked really hard for over a year on something that almost no one will be interested in reading. It was an astounding amount of work, comparable to making a record, from songwriting and rehearsing to mastering. And a lot more work than some records. This was not a punk record.

Well, since I just said not to read it after I’ve been posting about it for months, I guess I should at least summarize it. Here we go:

Social power is power over other people. Any kind of power. There is a lot of research on what having social power does to you, and it’s mostly bad: more stereotyping, less perspective taking, seeing others as a means to your ends etc. It’s the kind of stuff that might keep powerful people in power. Reading this stuff is pretty alarming for a feminist like me. It’s way more complicated than that, of course, but you’re getting the super short version here.

Personal power is power over yourself. There hasn’t been much research on its effects, just enough to suggest that it’s what people really want when they are struggling for power over each other, the real goal is self-governance.

I tried to test whether personal power has similar or different effects on perspective taking than social power. I was not able to do that, for complicated reasons. I was, however, able to find evidence that people consider personal power a broader category than social power. That is, you can sink to greater depths and rise to higher heights of personal power than you can social power. Second, I found that without a salient reminder of personal power, people did not make a distinction between social and personal power. That’s pretty interesting, because if people are out there trying to claw their way up the hierarchy, it may just be because they haven’t made the distinction between what they probably really want–personal power–and what they are working for–social power.

That may seem intuitive and like “why would you want to spend a year finding evidence for something so obvious?” but for a scientist, coming across something that seems obvious that hasn’t been tested is a gold mine. All kinds of obvious things have turned out to not be true. That’s one cool thing about psychology–it’s a baby science, so those unlooked-at areas are all over the place. There is only one other scientist that I’m aware of that’s looking into this subject too, Marius Van Dijke, in the Netherlands. Luckily, he’s got resources and will likely have much more traction on it than I could as an undergrad with one year to work and a $100 budget.

[First published on Nathen’s Miraculous Escape, June 12, 2009.]

The Relationship between Clarity of Enunciation and Idea Density

[First published on Nathen’s Miraculous Escape, June 12, 2009.]

Abstract

This study was an attempt to determine whether there is a relationship between individuals’ clarity of enunciation, rated subjectively, and linguistic ability, measured as idea density, as in Findings from the Nun Study (Riley, K. P., Snowdon, D. A., Desrosiers, M. F., & Markesbury, W. R., 2005; Snowdon, D. A., Kemper, S J., Mortimer, J. A., Greiner, L. H., Wekstein, D. R., & Markesbury, W. R., 1996). Idea density, the number of propositions per 10 words, had no significant correlation with clarity of enunciation in 33 digitally videotaped dyadic conversations between adult participants.

The Relationship between Clarity of Enunciation and Idea Density

Since 1992 I have wondered whether exceptionally clear enunciation was an indication of intelligence. I seemed to notice enhanced and separated consonants more often in those that I considered radically intelligent. My Organic Chemistry teacher, for example, said the word “little” exactly as written, with the crisp, unvoiced, alveolar stop [t], and not, as most other people said it, sounding like “lid’l.” Also, if he said a word that ended in a stop consonant followed by a word that started with a stop consonant, he stopped for each consonant; in “stand together,” the [d] and [t] would be separate, not, as in others’ speech, “stantogether.”

There has apparently been no research on a possible connection between cognitive or linguistic ability and clarity of enunciation. Most speech clarity research has focused on intelligibility, in relation to speech disorders, or dysarthrias, of various kinds on the speech-production side (e.g. Ansel & Kent, 1992), or with hearing impairment and hearing aids on the reception side, (e.g. Amyn, Rakerd, & Punch, 2006). There is also some research on the effects of the increased speech clarity in infant-directed speech, on early language acquisition. In infant-directed speech, for example, mothers’ vowel sounds were found to be more distinct from each other than in normal speech (Kuhl, Andrusky, Chistovich, Chistovich, Kozhevnikova, Ryskin, Stolyarova, Sundberg & Lacerda, 1997), and the more distinct the vowel sounds were, the better their infants’ speech perception (Liu, Kuhl, & Tsao, 2003). Whether distinctly produced speech is correlated with any other traits or tendencies of the speaker, though, appears to have gone uninvestigated.

Idea density

Having no direct measure of cognitive ability available, this study used idea density as a proxy. Idea density is a measure of linguistic ability that is associated with knowledge, vocabulary, and education level, and is defined as the average number of ideas, or propositions, per ten words in a text (Snowdon, Kemper, Mortimer, Greiner, Wekstein, & Markesbury, 1996). A text with high idea density, then, is complex and provides the reader with a lot of information.

In linguistics, a proposition is an idea expressed in a narrative, and considered a basic unit of memory for texts (Kintsch & Keenan, 1973). Propositions include verb, adjective, and adverb phrases, noun and clause conjunctions, and indications of temporal and causal relations (Turner & Greene, 1977). Linguists can take a text and construct what they call a propositional text base, which is a list of propositions coded in such a way that all of the information from the original text can be reconstructed.

In a longitudinal study of 180 nuns who entered their convents between 1931 and 1943, the idea density of their autobiographies, written at an average age of 22, correlated with their cognitive functioning and neuropathology in their old age and at death: Lower idea density predicted decreased cognitive functioning, and dementia (Snowdon et al., 1996), low brain weight, cerebral atrophy, and the neural plaques and tangles associated with Alzheimer’s disease (Riley, Snowdon, Desrosiers, & Markesbury, 2005).

It would be useful to know if idea density is also correlated with something as easily recognizable as clarity of enunciation. To that end, the hypothesis of this study was that clarity of enunciation would be significantly and positively correlated with linguistic ability, as measured by the idea density in conversational speech.

Methods and results

Participants

Participants were 110 adults, recruited by undergraduate psychology majors at the University of Oregon for a required class project, and recorded in 55 dyadic conversations on digital video recorders of varying quality. Conversations were recorded in residences, not in a lab. Forty-four participants were excluded from analysis: 34 because the video file was either not provided, would not play, or did not match the accompanying conversation transcription, 4 because participants were eating during the conversation, 4 because they were non-native English speakers, and 2 because their longest utterances contained no more than two words. This left 66 participants (34 female) between the ages of 18 and 57 (M = 24.4, SD = 6.3), 3 Latino, 1 Native American, and 62 White. Education level ranged from less than high school to graduate degree. All participants signed informed consent forms and filled out simple demographics forms prior to being filmed. No formal debriefing was given.

Transcription

Ten minutes of each 15-minute conversation was transcribed by the student who recruited and recorded the participants, using Elan transcription software. Transcriptions were to include all speech by each participant during the 10-minute interval. The only punctuation marks used were [/] to indicate falling intonation at the end of an utterance, and [?] to indicate rising intonation at the end of an utterance. Annotations were composed of groups of utterances by a single participant separated by pauses of less than 2 seconds. Thus, an annotation could be of nearly any length, and could contain any number of utterances.

Idea density coding

Idea density was coded by the researcher, using the coding scheme presented by Riley et al. (2005), in which idea density is the average number of propositions per 10 words. Propositions include verb, adjective, and adverb phrases, noun and clause conjunctions, and indications of circumstance such as time, place, and causality. (See Appendix A for all coding schemes, and see Turner & Greene, 1973, for a thorough presentation of the construction of a propositional text base.)

For a very short example of proposition counting, consider the utterance “We’re going to see Meaghan’s art show.” This sentence contains 6 propositions: (a) the predicate phrase “We see show,” (b) “we” means the speaker and at least one other person, (c) the show is an art show, (d) the show is Meaghan’s, (e) this event is to happen in the future, and (f) the people meant by “we” will have to move to another location in order to see the show. Notice that even in this simple example there is some ambiguity; proposition (f) may or may not have been intended by the speaker.

For each participant, idea density was coded for the annotation of their speech closest to 10 seconds long. In cases where much of that annotation was taken up by laughing or unintelligible speech, the annotation closest to 10 seconds with the largest number of words was used. Annotations ranged from 17 to 51 words (M = 33.40, SD = 8.59), and formed a platykurtic distribution (kurtosis = -.69, SE = .58). Number of propositions ranged from 18 to 27 (M =18.30, SD = 4.46), and formed a platykurtic distribution (kurtosis = -.51, SE = .58). Idea density ranged from 3.6 to 7.2 (M = .56, SD = .08), forming a somewhat skewed (skew = -.14, SE = .3) and platykurtic (kurtosis = -.24, SE = .59) distribution. The levels of skew and kurtosis present were probably acceptable, all falling well within 2 standard errors.

Enunciation coding

Clarity of speech is usually coded using digital editors and spectrographic analysis to measure vowel space expansion and consonant enhancement. The limitations of this study, however, made it necessary to code enunciation more subjectively: Two coders, one of whom was the researcher, and neither of whom were blind to hypothesis, listened to the first 2 minutes of each conversation and coded the clarity of speech of each participant on a 3-point scale: 0 = noticeably unclear speech, 1 = average clarity of speech, and 2 = noticeably clear speech. The raters exhibited poor reliability (Cronbach’s α = .35), indicating the need for more training on the coding scheme, but, because of the time constraints of this study, each participant received a speech clarity score equal to the average of the two coders’ ratings as they were.

The averaged speech clarity scores had a mean of 1.40 (SD = .46) and formed a skewed (skew = -.46, SE = .30), platykurtic (kurtosis = -.52, SE = .60) distribution. The level of skew and kurtosis were probably acceptable, falling within 2 standard errors.

Results

The question under investigation was whether clarity of speech was correlated with linguistic ability, as measured by idea density, the average number of ideas per word, in the conversational speech of this sample. The answer is no, they were not. The correlation between clarity of speech and idea density was not significantly different from 0 (r = .03, p = .81). This indicates that clarity of speech and idea density were not related.

Idea density was also not significantly correlated with gender, level of education of the parents of the participant, or the number of propositions per annotation. On the other hand, idea density was negatively correlated with number of words spoken per annotation (r = –.38, p <.01), positively correlated with age of participant (r = .25, p = .04), and had a very marginal positive correlation with the education level of participant (r = .21, p = .09).

Clarity of speech was marginally correlated with only one other variable, level of participant education (r = .24, p = .06). See Table 1 for all correlation values.

Discussion

This study showed no support for the hypothesis that clarity of enunciation was positively correlated with linguistic ability. The dimensions may, therefore, be orthogonal.

It is true that the methodology used was limited in several ways. The quality of the sound recordings was highly variable. The coding of enunciation was subjective, unreliable, and coders were not blind to condition. Idea density was coded by one individual, so there was no way to check his reliability. Additionally, the difference between the correlations of enunciation and idea density for one coder (r = .173) and the other (r = –.157) was marginally significant (p =.06) using Fisher’s r to z transformations to make the comparison.

Clearly, these results may not be the best indication of the relationship between these two variables, and improved methodology might reveal different results. On the other hand, it may be prudent to look elsewhere for correlates of idea density. The only moderately strong correlation with idea density in this study, for example, was the negative correlation with number of words spoken. The idea that high rates of speech might indicate low verbal ability is somewhat counterintuitive and intriguing.

Another possibility is that the idea density coding used by Riley et al. (2005) and Snowdon et al. (1996) is not appropriate for conversational speech, or might need some modification; there may be ways that spoken and written language differ that need to be taken into account. One annotation in this sample (and which was not used for this reason), for example, contained only one word, “Yeah,” giving this participant an average of 10 propositions per 10 words. Surely, a tendency to speak in one-word utterances is not an indication of linguistic ability!

Other possible differences between written and spoken language are the prevalence of filler words and run-on sentences in spoken language. Here is an example from the sample: “No they were talking about Eddie/ And they were like OH YEAH EDDIE was getting a hold of me like he wants to say goodbye to all his homies before he goes/ And I was like they were like he hasn’t called you? And I was like no?” Chances are, had this passage been written instead of spoken, “said” would replace “was like” and “were like,” and the “and” at the beginning of 3 of the 4 utterances would not appear. Although in this case the changes would balance each other, it may be that on the whole, written and conversational language differ significantly in their average idea density, and perhaps even in the cognitive factors that produce high or low idea density in each. Unfortunately, Riley et al. (2005) and Snowdon et al. (1996) did not publish their idea density statistics (though not surprising, since they published in neurobiology and medical journals, not linguistics or psycholinguistics journals), or that analysis could have begun in this study.

Flawed as it is, this study represents the only evidence to date that I am aware of about the relationship between clarity of speech and linguistic ability, and, so far, it seems unwise to judge someone intelligent based only on the crispness of their enunciation.

References

Ansel, B. M., & Kent, R. D. (1992). Acoustic-phonetic contrasts and intelligibility in the dysarthria associated with mixed cerebral palsy. Journal of Speech and Hearing Research, 35,296-308.

Amlani, A. M., Rakerd, B., & Punch, J. L. (2006). Speech-clarity judgments of hearing-aid-processed speech in noise: Differing polar patterns and acoustic environments. International Journal of Audiology, 46, 319-330.

Kintsch, W. & Keenan, J. (1973). Reading rate and retention as a function of the number of propstitions in the base structure of sentences. Cognitive Psychology, 5, 257-274.

Kuhl, P.K., Andruski, J. E., Chistovich, I. A., Chistovich, L. A., Kozhevnikova, E. V., Ryskin, V. l., Stolyarova, E. I., Sundberg, U., & Lacerda, F. (1997). Cross-language analysis of phonetic units in language addressed to infants. Science, 277, 684-686.

Liu, H. M., Kuhl, P. K., & Tsao, F. M. (2003). An association between mothers’ speech clarity and infants’ speech discrimination skills. Developmental Science, 6, F1-F10.

Riley, K. P., Snowdon, D. A., Desrosiers, M. F., & Markesbury, W. R. (2005). Early life linguistic ability, late life cognitive function, and neuropathology: Findings from the Nun Study.Neurobiology of Aging, 26, 341-347.

Snowdon, D. a. Kemper, S J., Mortimer, J. A., Greiner, L. H., Wekstein, D. R., & Markesbury W. R. (1996). Linguistic ability in early life and cognitive function and Alzheimer’s disease in late life: Findings from the Nun Study. Journal of the American Medical Association, 275, 528-532.

Turner, A. & Greene, E. (1977). The construction and use of a propositional text base.University of Colorado, Institute for the Study of Intellectual Behavior; Boulder, CO.

Table 1

Correlations of all variables

Variables                    1.         2.         3.         4.         5.         6.         7.         8.         9.         10.

1. Propositions

2. Words                     .84**

3. Idea Density            .17       -.38**

4. Speech Clarity        -.04      -.07      .03

5. Coder 1 SC             -.08      -.20      .17       .88**

6. Coder 2 SC             .06       .15       -.16      .71**   .29*

7. Gender                    .05       .14       -.15      .08       .07       -.02

8. Age                         .12       -.01      .25*     .18       .21       .03       -.02

9. Participant Ed.        .11       -.03      .21       .24       .24       .16       -.16      .52**

10. Mother Ed.            -.08      -.01      -.13      -.03      -.01      -.04      -.02      .06       .23

11. Father Ed.             .04       .02       .03       .00       -.05      .04       -.08      .12       .28*            .47**

Note. SC = speech clarity. Ed. = education. Gender was coded 0 = female, 1 = male.

* Correlation is significant, p < .05

** Correlation is significant, p < .01

Appendix A

Idea density coding

The following from Turner and Greene (1977):

1. Modified arguments of predicate propositions

2. Connected arguments of predicate propositions

3. Predicate propositions

4. Modifiers of predicate propositions

5. Modified arguments of circumstantial propositions

6. circumstantial propositions

7. Other connective propositions within clause

8. Repeat

Enunciation coding

0 = noticeably unclear speech

1 = average clarity of speech

2 = noticeably clear speech

Gender coding

0 = female

1 = male

Education level coding

1 = Less than high school dimploma

2 = High school diploma

3 = Some college

4 = Undergraduate degree

5 = Some graduate school

6 = Graduate degree

Differentiating the Effects of Social and Personal Power

[First published on Nathen’s Miraculous Escape, June 11, 2009.]

Thanks to my advisor and collaborator, Sean M. Laurent, and my second reader, Sara D. Hodges

Abstract

The current research attempted to differentiate the effects of social power (i.e., having control of others’ outcomes) from personal power (i.e., control of one’s own outcomes) on variables related to perspective-taking. Using methodology adapted from Galinsky, Magee, Inesi, and Gruenfeld (2006), 224 participants were primed with high social power, high personal power, or low power, and then completed two perspective-taking measures. While these measures did not significantly vary with power condition, evidence was found that supports the differentiation of personal power from social power. Low power, as experienced by participants (rather than as manipulated) had a strong negative correlation with personal power, and a weak negative correlation with social power. Personal power and social power were not significantly correlated.

Differentiating the Effects of Social and Personal Power

To some extent, all human beings want power—even if it is just enough power to ensure one’s safety, allow oneself to prosper, and obtain or keep freedom for oneself and one’s groups. This desire for power, to get just enough or to get even more than one needs for one’s own comfort and safety, may explain the frequent power struggles that populate our history books. And given the strong desire humans have to attain power, it is no wonder that psychologists are fascinated with the construct; understanding power is central to understanding human behavior.

Social power

Power can be defined in many ways, but in psychological research it is usually defined in relational terms, and is called “social power.” Individuals are said to have social power when they can control the outcomes of another person, influencing that person’s states, providing that person with rewards, inflicting punishments on that person, or governing the flow of resources to that person (e.g., Fiske & Berdahl, 2007; Galinsky, Magee, Inesi, & Gruenfeld, 2006; Keltner, Gruenfeld, & Anderson, 2003; Smith & Trope, 2006). Common to all definitions of social power is that there exist relationships between people, where some people control and are important sources for valued resources for other people. These valued resources are not limited to any particular physical or social object; a valued resource might range from a kind word to a grade in a class, a promotion, an offer of protection, or a glass of water for a thirsty child.

The approach-inhibition theory of social power ties high and low power states to psychological approach and inhibition mechanisms (Keltner et al., 2003). According to this theory, people who are high in social power will tend to have an approach orientation, will typically experience more positive affect, and will be trait-congruent—that is, they will act in alignment with their own traits, be less careful, more automatic in their social cognitions, and attend primarily to elements of the environment which might be useful or pleasurable, including a tendency to see others as a means to their own ends. People who are low in power, on the other hand, will tend to have an inhibition orientation, where they tend to experience more negative affect, be more cautious and observant of potential risks in their environment, and tend to see themselves as means to others’ ends.

Research has provided some support for approach-inhibition theory: Compared to people low in power, people high in power have been found to be more trait-congruent, more sensitive to potential rewards, and to experience more positive affect (Anderson & Berdahl, 2002). They are more prone to take risks and be optimistic about risk outcomes (Anderson & Galinsky, 2006). Higher power has also been associated with increased abstract information processing (Smith & Trope, 2006), increased reliance on the availability heuristic (Weick & Guinote 2008), and increased stereotyping (Fisk, 1993), while low power has been shown to increase metastereotyping (Lammers, Gordjin, & Otten, 2008) and impair executive functions (Smith, Jostmann, Galinsky, & van Dijke, 2008). Supporting an approach orientation, high power is associated with a tendency to act rather than not act (Galinsky, Gruenfeld, & Magee, 2003), to be more expressive (Snodgrass, Hecht, & Ploutz-Snyder, 1998), and to be less influenced by a variety of situational variables such as pressure to conform (Galinsky, Magee, Gruenfeld, Whitson, & Liljenquist, 2008). Furthermore, high power has been linked to devaluing others’ work for self-gain (Kipnis, 1972), to more extreme, less accurate judgments of opponents (Keltner & Robinson, 1997), and in some cases, to sexual harassment (Bargh, Raymond, Pryor, & Strack, 1995).

While many of the behaviors associated with power are self-serving and might serve to entrench power holders in their positions, at least some of these effects can be shifted by values and accountability; for example, individuals with a communal relationship orientation were found to be more generous when primed for high power (Chen, Lee-Chai, & Bargh, 2001), and familial responsibilities reduced several kinds of risky reward seeking in high need-for-power individuals (Winter & Barenbaum, 1985). It may also be true that some effects may not be the direct result of having power—instead they may be the result of the responsibilities that come along with power: For example, high power individuals have been shown to be better at individuating others unless burdened with organizational responsibility (Overbeck & Park, 2001).

Personal power

Van Dijke and Poppe (2006) asserted that striving for power is better explained by distinguishing between social power (i.e., having control of others’ outcomes) and personal power (i.e., having control of one’s own outcomes). While social power is related to authority, status, and dominance (Hall, Coats, & LeBeau, 2005), personal power is also related to autonomy, independence, agency, and competence (Overbeck & Park, 2001; Van Dijke & Poppe, 2006). Van Dijke and Poppe presented evidence that, given the choice, individuals act to increase their personal power instead of their social power, and will at times even voluntarily reduce their own social power to obtain personal power. Van Dijke and Poppe argued further that when individuals act to increase their power over others, they are motivated not by a wish to control others, but by a wish to not be controlled by others, and that increasing social power is a means to that end.

While most researchers have been careful to define power in social terms, it is evident that personal and social power have at least sometimes been confounded in research on the psychological effects of having power. That is, because personal and social power may tend to vary together, if they are not carefully separated, the effects of one type of power may be masked by the effects of the other. This may be especially true in experimental paradigms where social power is manipulated by giving some participants control over others or where the idea of control over others is primed. In these cases, personal power might be inadvertently manipulated at the same time. For example, one commonly used power-priming manipulation is to have participants write about a time in which they had power over someone else, or when someone else had power over them. While manipulating social power, this manipulation will tend to prime personal power as well, because people low in social power will tend to have less control of their own outcomes than do those high in social power, and those high in social power will tend to have more power over their own outcomes. This leaves open the possibility that any observed effects of this power manipulation could be due to the participants having control of others’ outcomes, having control over their own outcomes, or some combination of the two.

If personal power is the most likely reason that people seek power over others, then it is important to distinguish the effects of personal power from the effects of social power. It may be that having social power is associated with more negative or antisocial outcomes than is having personal power. If this is true, then encouraging people to seek personal power but not social power may be indicated.

Power and perspective-taking

Perspective-taking, conceptualized as the act of imagining or ability to imagine the experiences of others (Galinsky et al., 2006), is an important skill, associated with social competence and self-esteem (Davis, 1983). It is considered a necessary component of moral development and moral reasoning (Kohlberg, 1976; Walker 1980), and of empathy (Eisenberg, Murphy, & Shepard, 1997). Furthermore, perspective-taking has been linked to reductions in stereotyping (Galinsky & Moskowitz, 2000), increases in self-other overlap (Davis, Conklin, Smith, & Luce, 1996), and helping behaviors (Batson, 1991).

Perspective-taking, then, is clearly a beneficial behavior, and a necessary part of healthy social functioning. Social power, however, seems to have a negative effect on the ability to take others’ perspectives; Galinsky et al. (2006) found that after participants were primed with social power, they were less likely to take an outside visual perspective (i.e., less likely to draw an “E” on their foreheads in the direction that would be easily readable from another person’s perspective), less able to recognize other people’s facial emotional expressions, and were more likely to believe that others knew what they knew, even when they were presented with contrary evidence.

The present research

The purpose of the current research was to take a preliminary step toward differentiating the effects of having social and personal power on perspective-taking. Toward this end, Galinsky and colleagues’ (2006) methodology was used and extended somewhat, in order to test hypotheses about personal as well as social power. In the original paradigm, participants were first primed for either high social power or low power by writing a power-related essay. In the current paradigm, another condition was added where participants were primed for personal power. Following the priming tasks, participants performed one of two perspective-taking tests (these were also the same dependent variables used by Galinsky et al., 2006). One of these was the Diagnostic Analysis of Nonverbal Accuracy for adult faces (DANVA; Nowicki & Duke, 2001). In this test, participants view photographs on a computer screen, and are asked to identify the emotions shown on facial expressions of the photographed target. This task is thought to be a measure of interpersonal sensitivity related to perspective-taking, because the ability to recognize what emotions others are feeling is an important part of being able to take their perspectives. The other task asked participants to draw an E on their own foreheads; this measure assesses whether participants tend to spontaneously adopt the visual perspective of a person facing them, rather than their own internal perspective.

As a first outcome, we expected to replicate the work of Galinsky and colleagues, showing that the high social power group would perform worse on the DANVA and draw Es from their own perspective more often than the low power group. In terms of what personal power would predict, our hypotheses were not as clear. It was possible that personal and social power would activate approach equivalently and thus have the same effect on perspective-taking. It was also possible, however, that personal power would affect perspective-taking more negatively than social power, because people in the personal power condition might be less cued in to relationships with others. We reasoned, however, that the personal power group would perform somewhere between the low and social power groups on measures of perspective-taking, because similarly to social power, envisioning personal power should create associations with rewards and freedom, but different from social power, it should not contain the same dominance or hierarchy power cues.

Method

Participants

Two hundred and twenty-four undergraduates (172 females) from the University of Oregon’s Psychology and Linguistics human subjects pool participated in this experiment. The mean age was 19.6 years and the age range was between 17 and 49 years. In addition to partially fulfilling course requirements by participating, participants received entry into a lottery drawing for $100.

Measures

Participants each drew an E on their own foreheads as a measure of perspective-taking (Galinsky et al., 2006; Hass, 1984). An E that read in the correct direction for an outside observer facing the participant was treated as an indication that perspective-taking had occurred. This was presented to participants as a coordination task, rather than a test of perspective-taking. For a full description of the methodology, see Galinsky et al. (2006).

Participants also completed the Diagnostic Analysis of Nonverbal Accuracy (DANVA2-AF), a task where participants guess the emotions shown in 24 photographs of young adults’ faces: happiness, sadness, anger, or fear (Nowicki & Duke, 2001). Each image appeared on a computer screen for 2 seconds, followed by 5 seconds for the participant to mark their answer on a paper test form.

Next, participants completed four questionnaires that had been slightly modified from their original forms such that participants were instructed to respond based on how they were currently feeling, rather than assessing themselves globally. The first of these was a measure of Unmitigated Agency (UA; Spence, Helmreich, & Holahan, 1979), focusing on the self to the exclusion of others. On this scale, participants rated themselves on a five-point scale anchored by two contradictory characteristics (e.g., “Not at all arrogant” and “Very arrogant”).The second was the WHO-5 Well-being Index (WHO-5; Bech, 1993), where participants responded to questions such as “I feel cheerful and in good spirits” on a 5-point scale anchored by “Does not describe the way I feel at all” and “Describes how I’m feeling well.” The next questionnaire was Hegelson’s Unmitigated Communion Scale (UC; Hegelson & Fritz, 1998), which measures a focus on others’ needs to the detriment of the self. Participants responded on a five-point scale anchored with “Strongly agree” and “Strongly disagree” (e.g., “I always place the needs of others above my own.”)The last measure assessed conservative attitudes (Short Right-Wing Authoritarianism Scale; RWA; Altemeyer, 1998; Zakrisson, 2005). In this measure, participants rated their agreement with statements such as, “Our country needs a powerful leader, in order to destroy the radical and immoral currents prevailing in society today,” on a six-point scale anchored with “Strongly agree” and “Strongly disagree.” One additional, single-item measure of self-esteem was used: “How much do you like your name, in total?” This was measured on a 9-point scale, and was taken from Gebauer, Riketta, Broemer, and Maio (2008), who found that higher scores on this single-item measure indicated higher self-esteem.

As a manipulation check, participants rated themselves on several power-related adjectives or short statements (7-point scale where 1 = “Not at all” and 7 = “Extremely”). The following adjectives were used: High Social Power—dominant, in-charge, leader, organizer; High Personal Power—self-directed, independent, controls own choices, free; Low Power—accountable (reverse-scored), submissive, restricted, powerless. As an additional manipulation check, participants completed a post-experimental questionnaire about how powerful they actually felt during the manipulation. Questions included, “As you wrote about your life, to what extent did you feel as if you had power over someone else?” and, “As you wrote about your life, to what extent did you feel as if another person had power over you?” Each of these questions was rated on a 7-point scale anchored by either “Not at all,” and “Very much,” or “I agree completely,” and “I disagree completely.” See Appendix A for the complete list. Demographic questions were also included.

Procedure

After giving written consent to participate, participants were run in groups of 1-4. In Study 1, participants were then seated at computers in separate rooms (in Study 2, participants were first informed about a $100 drawing and resource allocation task—see below). Participants were randomly assigned to one of three conditions: high social power (HSP), high personal power (HPP), or low power (LP). HSP and LP participants completed an experiential priming task commonly used to manipulate a sense of high or low social power (Anderson & Berdahl, 2002; Galinsky et al., 2003; Galinsky et al., 2006; Smith & Trope, 2006) in which they wrote about a time when they had power over someone (HSP) or when someone had power over them (LP). HPP participants wrote about a time when they could do whatever they wanted, without interference. See Appendix B for the complete set of instructions.

Study 2 added a second task to amplify the prime (Galinsky et al., 2006). HSP participants were instructed that they had been randomly assigned to a “resource allocation task” in which they were to divide seven chances to win in a drawing for $100 between themselves and one other randomly selected participant. LP participants were instructed that they had been assigned to the resource allocation task, but were not to do the allocating. Instead, they would guess how many chances out of 7 another participant would give them. HPP participants were not assigned to the resource allocation task, but asked which of several prizes they would prefer, should they win the drawing. See Appendix C for the full text of these tasks.

Following this, participants completed the “E” task and the DANVA, counterbalanced. Next, participants responded to the questionnaires described above: UA, WHO-5, UC, RWA, adjectives, and self-esteem measure. This was followed by the post-experimental manipulation check questions and demographics questions, as well as written suspicion probes. Participants were then probed for whether they had guessed the connection between the manipulation and measures debriefed, thanked, and excused.

Results

The central research question of this study was how personal power would affect perspective-taking compared to low power and social power. To address this, participants were primed with either low power (LP), high personal power (HPP), or high social power (HSP). Based on past research (Galinsky et al., 2006), we expected high social power to decrease perspective-taking relative to low power. Additionally, we hypothesized that high personal power would decrease perspective-taking, but not to the same extent as high social power.

Contrary to our hypotheses, the primary dependent variables (the direction participants drew their Es and scores on the DANVA), did not vary significantly across condition. Because previous research (i.e., Galinsky et al., 2006) has shown that the same methodology used in the current study reliably affected perspective-taking, we undertook to discover why this finding was not replicated in our sample. As a first step, we assessed the reliability of the DANVA. This analysis revealed low internal reliability of the measure (Cronbach’s α = .345). To improve the reliability of the measure, we used the criterion of removing any item that had an item-total correlation lower than .1 (see Patterson & Stockbridge, 1998, for a similar method). Eleven of the 24 DANVA items were thus removed, based on this criterion, increasing reliability to .49. The item-total correlation of one further item dropped below .1 after adjusting the scale, so this final item was removed, leading to a final scale that contained 12 items. The reliability of the adjusted DANVA was still low compared to the alpha of .77 reported for college students by Nowicki and Carton (1993), but improved somewhat (Cronbach’s α = .504). Rerunning the previous analysis using the adjusted DANVA, however, returned the same result: no significant differences across condition in DANVA scores.

Next, we assessed whether there were any significant differences across conditions on any of the questionnaire measures that were included (UA, UC, WHO-5, RWA, Self-esteem). Although the majority of these questionnaires did not differ, the global self-esteem measure that asked participants how much they liked their names differed significantly across conditions, F(2, 217) = 5.79, = .004. Post-hoc tests revealed that participants in the low power condition (M = 7.80,SD = 1.52) liked their names significantly more than participants in the high personal power (M= 7.34, SD = 1.80) and high social power (M = 6.75, SD = 2.21) conditions, = .005, and that the high personal and high social power conditions differed marginally, = .058. That is, as measured by name-liking, LP participants had significantly higher self-esteem than both HPP and HSP participants, and HPP participants had marginally higher self-esteem than HSP participants. That self esteem varied by condition is most likely a contrast effect. Intuitively, participants primed with low power should have lower self esteem than those primed with high power, unless being made to think of themselves as low in power caused them to react and reassert themselves, increasing name-liking. This idea is supported by other research, where well-being and self-esteem were positively correlated, and name-liking predicted well-being better than explicitly measured self-esteem (Gebauer et al., 2008), while in this study, name-liking was positively correlated with well-being only in the HPP condition.

Manipulation Check

Because our primary hypotheses were not supported, and improving the reliability of the DANVA did not affect this finding, we turned to another idea: Perhaps the reason for the null effect is that power was not reliably manipulated. To test this, we checked the effectiveness of our manipulation, which had been assessed in two ways. On one questionnaire, participants rated themselves on a series of low, personal, and social power-related adjectives. On another questionnaire, participants answered either two or three questions about how much low, personal, and social power they had felt during the power-priming task.

Correlations between the four power-related adjectives and the questions meant to assess each type of manipulated power were examined. In each case, the correlations supported averaging measures together, forming three final composite manipulation check scales. For each, the reliability was adequate (low power α = .63, personal power α = .61, social power α = .64). Next, three separate one-way analyses of variance (ANOVAs) were run for each of the composite measures.

In the first, the composite measure for low power differed significantly across condition, (2, 178) = 20.32, < .001. Post-hoc tests showed the low power condition (M = 3.57, SD = 1.14) scored significantly higher (ps < .001) than the high personal power (M = 2.47, SD = 1.07) and high social power (M = 2.58, SD = .93) conditions, which did not differ from one another. That is, participants in the low power condition felt significantly less powerful than participants in the other two conditions, who did not differ in their experience of low power.

In the next analysis, the composite measure for personal power also differed significantly across condition, (2, 178) = 8.69, < .001. In this case, the low power condition (M = 4.63, SD = 1.05) scored significantly lower than the personal power (M = 5.36, SD = 1.04) and social power (M = 5.23, SD = 1.01) conditions (ps < .005), and again, the personal and social power conditions did not differ. That is, participants in the low power condition felt less personal power than participants in the other two conditions, which did not differ.

Last, on the composite measure of social power, the three conditions again significantly differed,(2, 178) = 12.415, < .001. Post-hoc tests revealed that on this measure, participants in the social power condition (M = 4.14, SD = 1.00) felt significantly more social power than participants in the personal power (M = 3.28, SD = 1.05) and low power (M = 3.44, SD = .97) conditions (ps < .001), which did not differ in the amount of social power they felt.

This pattern of results suggests that the experimental manipulation had the intended effects: Participants in the low power condition felt less powerful than participants in the other two conditions, and also felt less personal power than participants in the other two conditions. At the same time, on both of these measures, participants in the personal and social power conditions did not differ, as expected. On the last measure, which assessed feelings of social power, people in the social power condition felt like they had more power over others than did participants in the low power and personal power conditions, which did not differ.

Exploratory Correlational Analyses

After finding that the results of our primary tests did not support past research or our hypotheses, we decided to explore the data further. For example, although the manipulation check measures suggested that people in the different conditions actually did experience power in different ways, it is possible that the subjective experiences of power as measured by the manipulation checks themselves (i.e., rather than the manipulation) might shed some light on the differential effects of low, personal, or social power on perspective-taking and other outcome measures. Examining patterns of correlations between the manipulation check composite items (i.e., experienced power) and other variables allowed us to explore these questions.

Initially, correlations of the experienced power items (i.e., the composite manipulation check items) with each other were computed. As can be seen in Table 1 (along with the correlations of all the major variables), low power was negatively correlated with both social power (r = -.14, p= .055) and personal power (r = -.55, < .001). Although personal and social power were not significantly correlated across condition, within conditions, an interesting pattern emerged. In the social power condition, there was a significant and positive association between personal and social power (r = .39), but in the personal power condition, they were negatively correlated (=

-.21). These correlations significantly differ using Fisher’s r to z transformation, z = 3.34, p < .001. This provides further evidence that the experience of personal and social power can be differentiated, and that the manipulation served to do so effectively (see Table 2 for correlations of measures within conditions). This suggests that participants who had been reminded of a time when they were in control of themselves evaluated social power differently than those reminded of a time when they had power over someone else; in the social power condition, personal and social power were associated, but in the personal power condition, they were negatively associated. Perhaps, from a standpoint of social power, more social power means more freedom, but from a standpoint of personal power, more social power just means more responsibility.

Discussion

The current study set out to determine how personal power, a type of power that in the literature has been potentially confounded with social power, would differentially affect perspective-taking compared to social power and low power. We hypothesized that, as in past research (Galinsky et al., 2006), participants who were primed with social power would exhibit less perspective-taking than people primed with low power. In addition, we hypothesized that being primed with personal power, or the feeling of not being under anyone else’s control and able to take charge of one’s own destiny, would have effects on perspective-taking somewhere between the two. Our results, however, did not support these hypotheses. The primary dependent variables—the direction of an E drawn by participants on their own foreheads and a facial emotional expression recognition task—did not significantly differ across condition. Further exploration of the data, however, did allow a few conclusions to be drawn.

Using composite measures of power that were created from what were originally manipulation check items, it appears that there are some clear distinctions between social and personal power, particularly in how each type of power relates to the experience of not having power at all. In support of this, experiences of low power and high personal power were strongly negatively correlated, while low power and high social power were only marginally correlated. This was true even though the definition of low power provided was in terms of social power: being under the control of someone else. This indicates that low power and personal power might be part of a single dimension, while low power and social power are less related. This supports the view that personal power is a broader category than social power. Furthermore, it suggests that similarly to how people may seek social power as a way of increasing their personal power (e.g., Van Dijke & Poppe, 2006), people who have little power also are less concerned about others having power over them than lacking power over themselves. In further support of this, the same social and personal power measures were positively correlated in the social power condition, and negatively correlated in the personal power condition, indicating that participants primed with social power failed to make a clear distinction between social and personal power, while participants primed with personal power not only made the distinction, but conceived of the types of power as negatively related. If this finding can be strengthened by future research, it could have implications for power theorists: Not only do people seem to prefer personal to social power (Van Dijke & Poppe, 2006), but a reminder of personal power is all it takes to make the distinction salient. 

Although it is difficult to interpret null results, the lack of significant findings in this case implies several possibilities. It is possible that, despite our best efforts, our experimental procedure was flawed in some way. For example, some element in our instructions may have been restricting the range of outcomes for the DANVA scores and E direction: In the previous research that we were trying to replicate by using this design element, Galinsky et al. (2006) found that 33% of participants in the high social power condition drew a self oriented E compared to 12% for the low power participants, while we found 29% of high social power participants drew a self-oriented E and 31% of low power participants, a difference in magnitude that was not only much smaller, but in the opposite direction. Galinsky and colleagues also found that high social power participants made an average of 4.54 errors on the DANVA and low power participants made 3.11, while we found that high social power participants made an average of 4.20 errors, and low power participants made an average of 4.16 errors. These differences suggest that while the social power manipulation might have had the intended effect, participants in the low power condition did not respond in the same way in the current study as in Galinsky et al. (2006).

Another possibility is that the relationship between power and perspective-taking, at least as perspective-taking is measured by the variables used here and in Galinsky et al., may not be a stable one. It may be subject to change, for example, based on minor situational variables such as the wording of auxiliary instructions. Last, our inability to replicate past research on the topic might imply a difference between the populations of the human subjects pools at the University of Oregon who take part in studies for partial class credit, and the paid participants found at business and public service graduate schools used by Galinsky and colleagues. Perhaps power was particularly salient to their population or particularly unimportant to ours.

Personal and social power

One limitation of this research is that personal and social power were still confounded in both the low power condition and the high social power condition. Ideally, some way might be found to further disentangle these types of power, although this might be difficult. Theoretically, low and high social power are not distinct from personal power, but social power is one of the routes by which people seek personal power. The question of whether it is possible to separate these effects may depend on how we conceptualize personal power.

Personal power, or the ability to control one’s own outcomes, has been related to independence, agency, competence, feelings of expertise, autonomy, and personal causation (Overbeck & Park, 2001; Van Dijke & Poppe, 2006). Personal causation, “the initiation by an individual of behavior intended to produce a change in his environment” (DeCharms, 1968, p. 6), is related to personal power, but only tangentially so; an individual with personal power would likely exhibit this initiating behavior, but the behavior is not synonymous with personal power. Agency defined as self-efficacy (see, for example, Bandura, 1989, and Van Dijke & Poppe, 2006) is very closely related to personal power, but another psychological definition of agency—as a focus on self and separation (e.g., Abele, Uchronshi, Suitner, & Wojciszke, 2008; Ghaed & Gallo, 2006; Hegelson & Fritz, 1999)—confuses the issue in much the same way that operationalizing social power as dominance orientation has been a problem for social power theorists (e.g., Hall et al., 2005). Similarly, autonomy, which is commonly understood to mean self-governance, is a near synonym of personal power. Self-determination theorists, however, distinguish autonomy, defined as the extent to which an individual personally endorses the activities they engage in, from independence, defined as the extent to which people are reliant on others’ resources, assistance, or permission (e.g., Chirkov, Ryan, Kim, & Kaplan, 2003; Ryan & Deci, 2000). This leaves open the possibility that individuals whose behaviors are tightly controlled by others, but who enjoy the tasks they are given, or who feel that the control is justified and wise, could be labeled personally powerful, which stands in contrast to our working definition of personal power.

It may be then that personal power needs to be defined as a combination of other factors: In order to control one’s own outcomes, there must be the freedom to do so (i.e., independence as defined above), but also the ability to do so, or competence. If this is the case, then only one of these preconditions to personal power is confounded with social power—the extent to which we have independence is constrained by the social power others hold over us, while competence is a dimension of personal power unrelated to social power.

With this understanding of personal power, it may be possible in future research to create experimental conditions of both high and low personal power that do not vary as a function of social power. One possibility is using a manipulation of task difficulty, as in studies on the effects of control deprivation (Ric, 1997; Ric & Scharnitzky, 2003) and learned helplessness (Hiroto & Seligman, 1975; Simkin, Lederer, & Seligman, 1983). In these paradigms, participants in a “no-control” group are given some form of unsolvable task, putting them in a position of non-social, low personal power; their inability to control their own outcomes stems from the difficulty of the task, not from the control of someone else. A symmetrical non-social, high personal power condition could be created using practice to achieve competence at a task, or relative mastery of a task as a quasi-independent variable.

In its two-faceted sense, personal power is a broad concept, including social power as one of its limiting or enabling components. It should also be possible and instructive, however, to create experimental conditions in which social power varies independently from personal power. Participants in both low and high social power conditions could be instructed to perform the same task, perhaps relaying orders from superiors to inferiors in a hierarchy, and the number of superiors and inferiors could be manipulated: Low social power participants could be placed low in the hierarchy, with many superiors and only one underling, while high social power participants could be placed in the opposite position, second from the top, with many underlings.

There is also a need for control groups in power research. While high and low power are conceptualized as having symmetrical effects, with high power increasing positive affect and automatic social cognition, for example, and low power increasing negative affect and controlled social cognition (e.g., Keltner et al., 2003), most power research has not used control groups. In research that has used a control group, results have sometimes been asymmetrical. For example, in some experiments the low power condition was not different from the control, and in others it was the high power condition that was not different from the control (Smith & Trope, 2006). Without controls, it is impossible to tell whether it is high or low social power that is responsible for effects that are found, or whether the effects are symmetrical, as predicted by approach-inhibition theory. Control groups could also be helpful in determining what outcomes are a direct result of power and which are mediated by stress or mood.

Future research

How does personal power affect perspective-taking compared to social power? To the extent that these types of power are confounded, their effects will be equivalent, but it is also possible that their effects will remain equivalent even if they can be disentangled. Intuitively, personal power should produce an approach orientation. It may be, however, that personal power negatively affects perspective-taking more than social power: Personal power, on a broader continuum, has more extreme positions of power available; imagine being at the top of your hierarchy and a master of the skills required of you, versus at the bottom of your hierarchy and, additionally, inept. Social power, on the other hand, involving relationships by definition, may be associated with increased perspective-taking compared to personal power; at least someperspective-taking is necessary when dealing with subordinates. There is some evidence for this line of reasoning: Tjosvold and Deemer (1980) found that independence decreased perspective-taking compared to dependence, which in turn decreased perspective-taking compared to interdependence. To the extent that personal power is akin to independence, low power to dependence, and social power to interdependence, then, personal power should decrease perspective-taking more than low power, which in turn should decrease perspective-taking more than social power.

On the other hand, it may be that personal power affects perspective-taking less than social power does. The subjective sense of power has been shown to mediate at least some of the effects of social power (Anderson & Berdahl, 2002), and the cues of status and dominance that social power provides may be important to social power’s effect on perspective-taking.

Broadening our view beyond perspective-taking, this general line of research—distinguishing between the psychological outcomes of social and personal power—could be useful in expanding approach-inhibition power theory to include personal power. Many questions remain. Does high and low personal power come along with the same biological markers as social power, such as increased testosterone or glucocorticoids (Sapolsky, 2004)? How would a non-social, personal power condition compare to social power on measures of relative action, abstract thinking, stereotyping, executive functioning, and risk taking? In which areas are the effects of power the results of status and dominance cues and in which are they the results of freedom and efficacy?

The “empowerment” of oppression theorists such as feminists and other post-modern philosophers, anarchists and other libertarian philosophers, post-modern sociologists, and some alternative-education proponents, is often construed as more than just a human right. It is a benign form of power, (theoretically) coming with all of the benefits and few of the drawbacks and ethical quandaries inherent in hierarchical power. And empowerment, the ability of individuals and groups to be independent, self-governing, and to take part in decision-making processes, has much in common with personal power. Power corrupts, but empowerment does not. By distinguishing the psychological effects of having personal power and social power, we can begin to examine this assertion as an empirical question.

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Appendix A

Post-Experimental Questionnaire

All questions were answered on a 7-point scale. Questions 1 through 3 were anchored by 1 = “Not at all” and 7 = “Very much.” Question 4 was anchored by 1 = “Not at all powerful” and 7 = “Very powerful.” Questions 5 through 8 were anchored by 1 = “I agree completely” and 7 = “I disagree completely,” and reverse coded.

For the following 8 questions, please select the answer that best describes your experience.

1. As you wrote about your life, to what extent did you feel as if you had power over someone else?

2. As you wrote about your life, to what extent did you feel as if another person had power over you?

3. As you wrote about your life, to what extent did you feel as if you had power over yourself?

4. As you wrote about your life, how powerful did you feel?

5. As you wrote about a situation in your life, you felt as if you had control over someone else’s destiny.

6. As you wrote about a situation in your life, you felt as if someone else had control over your destiny.

7. As you wrote about a situation in your life, you felt as if you had control over your own destiny.

8. As you wrote about a situation in your life, you felt very powerless.

Appendix B

High Social Power Writing Task Instructions

On the next screen, you will be asked to spend about 5 minutes thinking about and writing about a time in your life when you felt like you had power over someone else. That is, you will write about a time when you had control over someone else’s actions or something that they wanted. Any time or event that fits this description will do. When it happened or the context in which it happened is not important – for example, it could concern school, family, work, or your personal life.

This task is important. Therefore, before continuing and writing about this time in your life, spend a moment RIGHT NOW to think of the time or event in your life that best fits this description. When you have this time or event firmly in mind, you may click “continue” and begin writing

Low Power Writing Task Instructions

On the next screen, you will be asked to spend about 5 minutes thinking about and writing about a time in your life when you felt like someone else had control over your actions or something that you wanted. Any time or event that fits this description will do. When it happened or the context in which it happened is not important – for example, it could concern school, family, work, or your personal life.

This task is important. Therefore, before continuing and writing about this time in your life, spend a moment RIGHT NOW to think of the time or event in your life that best fits this description. When you have this time or event firmly in mind, you may click “continue” and begin writing.

High Personal Power Writing Task Instructions

On the next screen, you will be asked to spend about 5 minutes thinking about and writing about a time in your life when you felt like you had complete control over your own life and were free to do whatever you wanted, without interference. Any time or event that fits this description will do. When it happened, or the context in which it happened, is not important – for example, it could concern school, family, work, or your personal life.

This task is important. Therefore, before continuing and writing about this time in your life, spend a moment RIGHT NOW to think of the time or event in your life that best fits this description. When you have this time or event firmly in mind, click “continue” to progress to the next screen.

 

Appendix C

High Social Power Resource Allocation Task Instructions

 

You have been assigned to the resource allocation task and are in charge of deciding how many tickets for the drawing for $100 that you and the other person involved in this task each will receive.

Decide on a division of 7 tickets between yourself and the other person:

7                      7 for yourself and 0 for the other person

6                      6 for yourself and 1 for the other person

5                      5 for yourself and 2 for the other person

4                      4 for yourself and 3 for the other person

3                      3 for yourself and 4 for the other person

2                      2 for yourself and 5 for the other person

1                      1 for yourself and 6 for the other person

0                      0 for yourself and 7 for the other person

Low Power Resource Allocation Task Instructions

 

You have been assigned to the resource allocation task, but you do not have control over the allocation of the tickets for the drawing. Instead, predict how many tickets the person making the allocation decision will take and how many will be given to you.

Remember not to pretend you are determining the allocation. You should try to predict what the person making the decision is going to do.

0          0 for you and 7 for them

1          1 for you and 6 for them

2          2 for you and 5 for them

3          3 for you and 4 for them

4          4 for you and 3 for them

5          5 for you and 2 for them

6          6 for you and 1 for them

7          7 for you and 0 for them

High Personal Power Resource Allocation Task Instructions

 

As part of this study, with your consent, you will be entered into a drawing at the end of the study. You will have seven full chances to win.

There are four prizes to choose from. Please choose which of these prizes you would prefer, should you win. If you choose number 4, a text box will open for you to specify which business you would like a gift certificate from.

1          $100 cash

Appendix C continued

2                      $110 gift certificate at Market of Choice on Franklin Blvd.

3                      Bose Triport In-Ear Headphones, worth $99.95

4                      $105 gift certificate to local or online business of your choice <specify>

5          Opt out of drawing

Table 1

Correlations and reliability (Cronbach’s α) of major variables

E           DANVA UC            UA         WHO-5      RWA     Name     LP comp   HPP comp  HSP comp

E

DANVA     -.039         .504

UC             -.028         .224*      .651

UA              -.075         -.195*     -.232*    .693

WHO         -5 .047      -.004       -.031      -.132*      .698

RWA          -.068         .058        -.021      .017         .065       .820

Name         -.122         .000         -.115      -.008        .121       .132

LP comp     .123          .159         .157*     -.001        -.225*    .011       -.011         .632

HPP comp  .021          .013         -.111      -.018        .201*     -.074      .046          -.554*    .608

HSP comp  -.006         .084       -.024      .109       .207*     .164*     .081          -.143      .089           .635

Note. Reliability coefficients are on the diagonal. E = E direction (coded 1 = perspective-taking, 0 = no perspective-taking); DANVA = adjusted DANVA scores; UC = Unmitigated Communion Scale; UA = Unmitigated Agency Scale; WHO-5 = the WHO-5 Well-Being Index; RWA = Right-Wing Authoritarianism Scale; Name = self-esteem measure; LP comp = composite low power measure; HPP comp = personal power composite measure; HSP comp = composite social power measure.

* Correlation is significant, p < .05

Table 2

Correlations of composite power variables with other dependent variables

Condition  ____

Variables LP HPP HSP Overall

LP comp HPP comp                   -.421a*    -.561a*    -.502a*    -.554a*

HSP comp                                    -.233a -.043a -.100-.143a

HPP comp  HSP comp              .089abc -.213a .388b*     .089c

E direction LP comp                 .212a .234a -.056a .123a

HPP comp                                   .021a -.112a .   160a .021a

HSP comp                                   -.098a -.171a .267b*     -.006ab

DANVA LP comp                      .020a .038a .397b*     .159ab*

HPP comp                                  .205a -.200b .115ab .013ab

HSP comp                                 -.139a .232.140ab .084a

UA          LP comp                     .040a .016.096-.001a

HPP comp                                 -.126a .042a -.061-.018a

HSP comp                                .146a -.008a .083.109a

WHO-5   LP comp                   -.142a -.278a*    -.369a*    -.225a*

HPP comp                                 .239a .204a .191.201a*

HSP comp                                .104a .219a .371a*     .207a*

UC          LP comp                    .303a*     .211a .143.157a*

HPP comp                                -.011a -.351a*    -.097-.111a

HSP comp                                 .039a      -.002a     -.135a     -.024a

RWA      LP comp                    -.043a .115a -.103.011a

HPP comp                               -.039a -.071a -.082-.074a

HSP comp                                  .135a .207a .223.164a*

Name-liking    LP comp         -.036a -.262a*    -.001-.011a

HPP comp                                 .005a .163a .126a         .046a

HSP comp                                  .026a .284a*     .128.081a

Note. Within rows, correlations with different subscripts differ significantly, < .05, using Fisher’s r to z transformations. LP comp = composite low power measure; HPP comp = personal power composite measure; HSP comp = composite social power measure. For condition, LP = low power condition; HPP = personal power condition; HSP = social power condition. DANVA = adjusted DANVA scores; UA = Unmitigated Agency Scale; WHO-5 = the WHO-5 Well-Being Index; UC = Unmitigated Communion Scale; RWA = Right-Wing Authoritarianism Scale; Name-liking = self-esteem measure.

* Correlation is significant, p < .05

An Important Lexical Retrieval Variable

I just read about two studies that found that humanities lecturers use more filled pauses–time saying ‘uh,’ ‘um,’ etc–than science lecturers, and that it’s probably because the humanities have more synonyms to draw upon. In science, it is very useful in conversation to have very precise, technical definitions of each word that everyone agrees upon. Empathy, for example, cannot mean or connote compassion in psychological discourse, and if it does, you run into problems.

Maybe that’s why the people in my social cognition lab (can) talk so fast. They all understand precisely each word, so ideas can come and go very rapidly. Still too rapidly for me to understand, sometimes.

[First published on Nathen’s Miraculous Escape, May 7, 2009.]

Reaction to Galinsky & Moskowitz, 2000

Stereotypes are not just ideas. They actually exist, like sinister puppeteers in our brains, pulling our strings at the sight of race, gender etc. Trying to suppress the puppeteers makes them stronger. One way to weaken them is by keeping your attention on taking perspectives: What would it be like to be that person? Not that kind of person, that specific person.

(Want convincing? See Galinsky, A. D., & Moskowitz, G. B. (2000). Perspective-taking: Decreasing expression, stereotype accessibility, and in-group favoritism. Journal or Personality and Social Psychology, 78, 708-724.)

[Reblogged from Nathen’s Miraculous Escape, April 30, 2009.]

Mental Effort

What is the sensation of exerting mental effort? It takes energy to think and focus attention, but we can’t directly feel what is going on in our brains. There are no sensory nerve endings in there. I can understand why we feel tired after thinking a lot, but I don’t understand why thinking hard feels effortful in the moment. It really does, though. Some of the thinking I’m doing feels like pushing a boulder up a hill, except more confusing, and my body aches with it–more than I would expect from just sitting and typing and looking at notes. My only idea is that I’m unconsciously flexing muscles when I think, especially in my face, neck, and back, and that produces the sensation of mental effort. What do you think? I’d sure like to be able to apply my brain fully without flexing any extra muscles.

[First published on Nathen’s Miraculous Escape, April 18, 2009.]

 

The Illusion of Control

[First published on Nathen’s Miraculous Escape, December 24, 2008.]

I do not believe in free will. I am what you might call a free-will agnostic. Hundreds of years of thought and debate have brought us no closer to agreement about whether an individual’s consciousness is capable of true agency. I can understand, though, how the idea that one might not control even one’s own actions is distressing; a perception of control makes stressful situations easier to cope with, while a perceived lack of control, and especially perceived loss of control, make stressful situations more distressing (Sapolsky, 2004). Note that it is our perception, however, not necessarily the reality of control, which is important. As it turns out, our perceptions of control are not reliable. The only situation in which we can be sure about how much control we have is when we demonstrably have no control at all, and in those situations people often still believe they have control.

Psychologists call this phenomenon the illusion of control: The tendency to overestimate how much control one has over an outcome. Participants in an experiment by Tennen and Sharp (1983), for example, believed that they controlled a blinking light about one third of the time, when in fact there was no connection between their button and the light. Even more surprising, experimental participants came to believe that they were good at guessing the outcome of the notoriously random coin toss (Langer & Roth, 1979). All it took were a few successes early on. Ellen Langer, in an early series of experiments (1975), found that the key to producing the illusion of control is the presence of skill cues, like practice, familiarity, choice, competition, and personal involvement. That is, if a task reminds you of a time when you used skill to influence what happened, you are likely to believe you have more control over the outcome of the task than you do. This tendency creates an inaccurate perception of reality which can have serious negative consequences but also may have beneficial effects.

The desire to be accurate in our perceptions and judgments is a basic human motivation, among psychological motivations second only to our need for self-esteem (Aronson, Wilkert, & Akert, 2007). This desire serves us well, especially in cases when a discovery of error on our part tempts us to distort reality to save our self-esteem; it would be much more difficult to learn from our mistakes if we were never compelled to admit them. In the case of the illusion of control, however, the mistaken belief in control will often not even come to our awareness. Usually there is no experimenter at the end of our task, gently debriefing us on how our button is not connected to the light. There are cases when the mistaken belief in control is benign enough—the experimental participants thinking they controlled a light were not hurting themselves or others, nor does a basketball player, swaying to the left, trying to move his shot toward the basket—but there are situations where having an inaccurate sense of control can be unfortunate.

The illusion of control can lead to overconfidence, a bad quality for those in dangerous or critical situations. A surgeon, for example, who believed she had more control over bleeding than she did, might kill her patient with a bad decision. Pilots overconfident in their control of an aircraft’s elevation or attitude are risking their own and their passengers’ lives. I expect that those who have lives explicitly in their hands are highly trained to know exactly where their control ends, so that they will take proper precautions, but it may be that the illusion of control causes injuries and fatalities in these and similar fields. And in less explicit situations, such as driving on the highway, the training may not be as thorough. A truck driver, for example, who fell asleep behind the wheel, likely did so believing that he had control over his staying awake. And even if life is not at stake, there can be loss; dice gamblers, for example, often believe that their strategy of playing increases their odds, when it demonstrably does not (Henslin, 1967, as cited by Langer, 1975). There may be interpersonal costs, too. If I believe that I am in control of a relationship, I might not give my partner the attention she needs, and eventually lose her. The illusion of control may play a part in addiction, too: The well-known first hurdle to recovery is admitting a lack of control.

I suspect that the best antidote to the illusion of control is to use knowledge of the phenomenon and how it operates to maintain skepticism about your level of control. Awareness alone should help. If the question of how much control I have comes up, I will be more skeptical, knowing that people tend to overestimate their level of control. The knowledge that the illusion tends to be stronger when skill cues are present should help, too: If I am feeling more confident about an outcome because I’ve had practice at a task or even because I am allowed to make a choice in it, this might trigger my memory of the illusion of control and lead me to carefully consider base rates. The trick is maintaining an empirical mindset, where questions like “How much control do I have here?” present themselves to the consciousness as questions, and knowledge of the ways we fools ourselves should help with that.

Another antidote to the illusion of control is more troubling: depression. It turns out that depressed people are realistic in their assessments of control where non-depressed people are not (Alloy & Abramson, 1979, as cited by Seligman, 2002). In another version of the blinking light experiment, non-depressed participants believed that they had control of the light about a third of the time, but depressed participants could tell that they had no control. This came to be called depressive realism. Happy people, on the other hand, tend to have a flexible locus of control. That is, they tend to believe that they are in control only when it serves their well-being to believe so. When things are going well, happy people will think they are responsible, but when things are not going well, they think that it is because of passing circumstances (Seligman, 2002). (Understand that this is not a conscious strategy, but a non-conscious tendency.)

It may be that depression causes depressive realism, but it also may be the other way around: A tendency to believe we have control keeps us from getting depressed, while a tendency to be realistic about control causes us to become depressed. Everyone is a victim of circumstances to some degree—social psychology is a mountain of evidence for that—and lack of control is stressful, especially if a situation is unpleasant. That stress may be ameliorated to some degree by an incorrect belief in control, as long as that belief has no serious negative consequences. In that case, the inability to fool ourselves may be the problem for depressed people. And if in fact we do not have free will, and any sense of control we have is illusory, that illusion may be what is keeping us happy.

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      Langer, E. (1975). The illusion of control.

Journal of Personality and Social Psychology, 32,

     311-328.
      Langer, E. & Roth, J. (1979). Heads I win, tails it’s chance: The illusion of control as a function of the sequence of outcomes in a purely chance task.

Journal of Personality and Social Psychology, 32,

     951-955.
      Sapolsky, R. M. (2004). Why is psychological stress stressful? In

Why zebras don’t get ulcers: The acclaimed guide to stress, stress-related diseases, and coping 

    (pp. 252-270). New York: Henry Holt.
      Seligman, M. E. (2002). Happy but dumb? In

Authentic Happiness, 

    (pp. 37-39). New York: Free Press.
      Tennen, H. & Sharp, J. P. (1983). Control Orientation and the Illusion of Control.

Journal of Personality Assessment, 47,

       369-374.

Social Psychology Journal: My Changing Bias

[First published Nathen’s Miraculous Escape, December 21, 2008.]
      I first took the race Implicit Associations Test (or “race IAT”), a test of non-conscious attitudes toward African Americans, several years ago after reading about it in Malcolm Gladwell’s Blink. In the IAT paradigm, a computer program measures how quickly you associate positive and negative words with African Americans compared to Whites. I was unhappy with the program’s conclusion, that I moderately favored Whites over African Americans, as this bias runs directly counter to my belief system. My disappointment and embarrassment were tempered somewhat, though, by the fact that Gladwell, an African American, reported receiving the same results that I had. Being implicitly racist is an effect of growing up in a racist society1; seventy percent of those who took the race IAT before me had been biased against African Americans to some degree (Project Implicit, 2008). This bias can change, though. Rudman, Ashmore, and Gary (2001), for example, found that race IAT scores improved for volunteers that took a seminar on prejudice and conflict who liked the African American teacher and formed friendships with African Americans during the semester.

      Although I seem to have a weak implicit bias as measured by the IAT, when it comes to my conscious beliefs, I have thought of racism as a big problem for as long as I have understood the concept. It is easy to trace the sources of that belief: First, I come from an egalitarian-minded family, for whom any assertion of differences between races was met with suspicion or contempt. My parents strictly controlled my media exposure, too;2 my two earliest memories of race in the media are watching Roots and a documentary on the Little Rock desegregation process. I remember being confused and enraged by the way people treated each other. Second, my closest friends throughout my life have been even more vehemently anti-racist than my parents, leading me to take part in just the kinds of discussions and self-examination that should lead to shifts in explicit prejudice (Rudman et al., 2001).

Implicitly, I’ve had more trouble, as my IAT results indicated, but that was more difficult to discern. I was in my 20s before I had an experience that revealed my non-conscious racism. I was waiting for my connection in the Sacramento Greyhound station at 4 am, very tired and anxious, and I dozed off for a moment. When I started awake, disoriented, I was vaguely afraid that someone had taken my bag, and scanned the room for who it might have been. My eyes went directly to the one African American man in my field of vision. Then I quickly realized two things. My bag was still with me, and the man I had looked at was a highly unlikely candidate for a thief. He was a middle-aged, conservatively dressed man, talking quietly with his three young children. I was embarrassed and disturbed. For the first time I had the sense that I was subtly possessed by racism. The stress I was experiencing had undermined my controlled processing, and so my implicit attitude had leaked out.3

The roots of my automatic stereotyping are also easy to see: I grew up in a rural, white town, with many racist peers and little opportunity to individuate African Americans. I did not seek out opportunities to do so, either, which left me prey to illusory correlations with stereotypes: Of the two African Americans my age, one happened to be the best break dancer I knew and the other the fastest sprinter. My high school had three African Americans attending, one of whom had a locker next to mine. He had a conversation with his twelve-inch penis every day as we got dressed for gym.4 Later, for college, I moved to a more diverse area, but also started seeing more TV and movies about gang violence and crime. There were also many super aggressive African American panhandlers in downtown Oakland, while I waited for my bus at night. There was when I worked in a restaurant in a poor, African American neighborhood in San Leandro; I remember reminding myself that it was all socioeconomics, but the fact that I could count on bigger tips, on average, from the White people who came in made it hard not to feel happier when they did.

On the other hand, most of my coworkers at that restaurant, whom I became very fond of, were also African American, and I spent a lot of time getting to know them individually. Many of my fellow students at the trade school I attended at San Francisco State were African American as well. Those situations provided me with all of the elements that should result in decreased prejudice against African Americans—mutual interdependence, common goals, equal status, many informal, interpersonal contacts, and a social norm of equality (Aronson, Wilson, & Akert, 2007, p. 451)—as well as the opportunity to change my implicit attitudes, as the participants in Rudman and colleagues’ (2001) seminar on prejudice had, by liking my African American supervisors and making friends among this “out-group,”5 during the same period that I had my two most anti-racist housemates ever, and lots of conversations about race.

During the period of my social psychology journal, I started thinking that I stood a good chance of doing better on the race IAT. During the last several years I have stepped up my thinking and emotional work around racism, and have also had more fortunate experiences: I’ve been in an Eliminating Racism support group and two of my favorite counselors are African American men. I had an African American man as a recording studio client, who, though a gangsta rapper, drug dealer, and pimp, I came to know as a sophisticated and complex person. I took a sociology class called America’s Peoples, which looked at the history of oppression in America and included a lot of class discussion. I took a Family and Human Services class called Diversity in Human Services, which was a series of lectures by minority speakers about what it was like to be a member of their group, again with a lot of discussion and introspection. Both of these classes had opportunities for perspective taking, which Galinsky and Moskowitz (2000) found to decrease both implicit and explicit stereotyping. I have good relationships with my honors thesis advisor and my practicum supervisor, both of whom are African American. Finally, I have been elated ever since the election of Barack Obama, an African American, to the presidency of the United States, and watching his speeches with great appreciation.

I was surprised and very frustrated to find that second attempt at the race IAT showed the same results as my first had: I moderately favored Whites over African Americans. Perhaps I shouldn’t have been surprised; it is notoriously difficult to change your score. On the other hand, the results of the test, as they are available online, are not very fine-grained; all response times are measured to the millisecond, but all that variability is funneled into seven categories—strong, moderate, mild, or no preference for or against African Americans. It was quite possible that I had come very close to improving my results without knowing it, so I engaged in counter-factual thinking. Perhaps I was a victim of stereotype threat; perhaps my fear of confirming the stereotype that White people are racist caused me to do so.6 Or maybe it had been sequence effects that had foiled me; the version of the test I had taken had started with negative words associated with African American faces. I thought that I would have done better if it had started with positive words associated with African American faces. But it hadn’t and I hadn’t.7

After I calmed down, I took an IAT for preferences between the presidential candidates, Obama and McCain, at the same time as testing preferences for Whites or African Americans. This time, the results said that I moderately preferred Obama over McCain, but also that I stronglypreferred African Americans to Whites. The IAT is supposed to be quite reliable, so I was surprised about the change8—something was going on that could change my results pretty radically. I started thinking that part of my score was my skill on the task—that one or more of my inept answers were serving as extreme outliers, 9 biasing my scores one way or the other. I took the race IAT for a third time, and this time scored as not biased at all, making me the happiest yet, but even more curious. Maybe I spiked my appreciation for African Americans by priming myself with images of Obama and McCain,10 and in the future my score would again show my moderate bias. Or perhaps my greater facility with the test had brought out my true non-bias.11 Or perhaps itwas the sequence effects, after all, because the third time had paired African American faces with good words first. Finally, if the results could vary this much, maybe my single attempt at the test years ago had been an aberration as well, misreporting my true bias or lack of bias.12

Over the next few days, I took the race IAT three more times, and each time scored the same—unbiased—so I feel pretty safe now to say that this is my true score. I feel pleased about that but I don’t believe that it means I am free from bias or prejudice toward African Americans. Strictly speaking, it just means that I don’t associate negative words like “hate,” “pain,” and “evil,” or positive words like “laughter,” “glorious,” and “love,” with images of African American faces any quicker than I do with images of White faces. Still, assuming that my first score of moderately biased was my true score of several years ago, it shows some progress—my non-conscious processes have caught up with my conscious beliefs to some degree. And even if my original score was misleading, I am still pleased with my unbiased score.

[Comments by instructor, Sean Laurent:]

Good you should be pleased. Still, there are ways, if one is consciously trying, to “beat” the IAT (there has been some discussion in the literature about this), such as described above.

This is a well-crafted paper, full of insight and very interesting to read. Did you actually keep a journal for the two weeks, or just reflect on implicit and explicit racism in your life as you wrote the paper. Either way, it came out well, and tells a very nice story, linking ideas in your life to specific experiences and showing that you have reflected on the topic. Well done. 48/50 I might like to use this paper as an example of a reaction paper that is done correctly.

1 Is it? This is kind of a sweeping statement – it implies that the problem of why people are implicitly racist is solved.

2 You might mention why this is important in terms of knowledge of racial stereotypes driving certain effects like shooter bias, etc.

3 Very vivid storytelling here.

4 That’s funny….

5 This last part seems tacked on and could be safely reorganized or made into another sentence.

6 Good point, possible.

7 Usually this doesn’t matter much.

8alternatively, it could be that you have very strong associations with Barak, and that while he was serving as an exemplar of the group, this overrode the automatic stereotyping)

9 Also possible.

10 Quite possibly.

11 Or you might have deliberately or unconsciously slowed your responses to BOTH categories in order to speed your pairings of whites with negative, etc.

12 Probably not. Remember, from articles like the shooter bias, that even a strong knowledge of the cultural stereotype can drive implicit effects, so…

References

      Aronson, E., Wilson, T. D., & Akert, R. M. (2007).

Social Psychology. 

    Upper Saddle River, NJ: Pearson Prentice Hall.
      Galinsky, A. D., & Moskowitz, G. B. (2000). Perspective-taking: Decreasing stereotype expression, stereotype accessibility, and in-group favoritism.

Journal of Personality and Social Psychology, 78, 

    708-724.
      Gladwell, M. (2005).

Blink

    . New York: Little, Brown.
      Project Implicit (2008). Retrieved November 16, 2008, from

https://implicit.harvard.edu/implicit/demo/background/faqs.html#faq22

       and

https://implicit.harvard.edu/implicit/Study?tid=-1

    .
      Rudman, L. A., Ashmore, R. D., & Gary, M. L. (2001). “Unlearning” automatic biases: The malleability of implicit prejudice and stereotypes.

Journal of Personality and Social Psychology, 81,

       856-868.

Reaction to “On the Confirmability and Disconfirmability of Trait Concepts”

[First published on Nathen’s Miraculous Escape, November 7, 2008.]

Some time ago, I was present for a conversation between two of my friends in which it came out that one had lied to the other. It was immediately clear that there was nothing the one who had lied could do to make the other believe anything else he said. It could easily take years of acting with perfect integrity, I thought, to build that trust back, if it could be built back. This is a major point of the article, “On the Confirmability and Disconfirmability of Trait Concepts,” by Rothbart and Park: Where favorable trait ascriptions, like “honest” and “truthful,” are easy to lose, unfavorable trait ascriptions, like “deceitful” and “deceptive” are difficult to lose. This is a problem not only for individuals like my friend who lied, but for whole groups of people laboring under the unjustly and inaccurately received negative trait ascriptions called stereotypes.

Rothbart and Park had participants rate 150 trait adjectives on how easy they were to acquire and lose in three dimensions: how often the environment provides opportunities to show or disprove each trait, to what extent each trait had clear, corresponding behaviors to indicate it, and how many times a behavior would need to be seen before a corresponding trait could be inferred or disproved. What they found in part was that two of the dimensions, the first and third were related to how favorable a trait was rated. That is, when it comes to how often the environment provides opportunities to show or disprove each trait, favorable traits are easy to get and easy to lose, whereas unfavorable traits are hard to get and hard to lose. On the dimension of how many times a behavior would need to be seen before a corresponding trait could be inferred or disproved, favorable traits were hard to get and easy to lose, where unfavorable traits were easy to get and hard to lose. Notice that in both of these relationships, unfavorable traits were difficult to lose; there are few occasions provided to disprove them, and disconfirming behaviors seem more ambiguous than confirming behaviors.

This pattern may apply to the traits ascribed to groups as well as those ascribed to individuals, as trait ascriptions are part of our schemas about individuals as well as groups. Schemas are cognitive information-sorting systems that function in part as filters on our perception, causing schema-consistent behaviors to be memorable and schema-inconsistent behaviors to go unnoticed more easily and be forgotten more easily, if noticed (Aronson, Wilson, & Akert, 2007). This may be a problem-compounding effect for those who are victims of a negative cultural stereotype.1 Rothbart and Park’s (1986) participants were not asked to consider race, and reported that it was difficult to imagine someone disconfirming a negative trait. It seems that it would be that much more difficult for a person of color to disconfirm a negative trait that coincided with the stereotype of their group. At least three factors would converge against it: The environment doesn’t provide many opportunities to disconfirm unfavorable traits, disconfirming behaviors are much more ambiguous than confirming behaviors, and stereotypers2 are less likely to notice disconfirming behaviors and more likely to forget them.

There is another troubling point. Rothbart and Park (1986) predicted that, once acquired, a negative stereotype will persist in a stereotyper’s mind unless they have contact with the stereotyped group, for otherwise there is no opportunity to observe disconfirming behavior. That reasoning is congruent with the evidence they collected, but is somewhat contrary to, or at least complicated by, the evidence collected by Correll, Park, Judd, and Wittenbrink (2002) investigating “shooter bias,” the increased tendency for experiment participants to mistakenly shoot African American target images more than white target images. The authors of this study found that the bias was predicted in part by the level of contact with African Americans. In keeping with Rothbart and Park’s prediction, increased contact with African Americans did correlate with decreased personal endorsement of stereotypes of African Americans, but also with this increased, non-conscious acting on a stereotype, that an African American is more likely to have a gun.3

There are caveats to consider in this line of thinking. First, “gun-possessing” was not among the traits rated by Rothbart and Park’s participants, and so it is a stretch to compare shooter bias with even the related traits that were included, like “violent,” “mercenary,” and “hostile.” Second, trait ascription may be more closely related to the personal endorsement of a stereotype than the unconscious application of a stereotype, like shooter bias. Third, Rothbart and Park used imaginability as their operationalization of their three major factors. In other words, to determine how many occasions the environment provides for confirming or disconfirming a trait, for example, they asked participants how easy it was to imagine such occasions for each trait. Though Rothbart and Park found that their operationalization provided reliable statistics in that they were stable from participant to participant, imaginability may or may not accurately predict how difficult a trait will be to gain or lose. Fourth, Rothbart and Park predicted that contact with a stereotyped group would be necessary to disconfirm a trait, which is probably true, but it does not follow that contact would be sufficient to disconfirm a trait.4

Still, that stretch is worth entertaining because of how closely all three elements, trait ascription, belief in stereotypes, and acting on stereotypes, are related conceptually. The possibility that contact with a stereotyped group could simultaneously be involved in decreasing belief in the stereotype while increasing the amount of unconsciously acting on the stereotype begs for more investigation. One possible place to start is to check if the effects replicate in other stereotypes, perhaps having participants rate job applications attributed to either whites or African Americans, to see how bias in the ratings might correlate with participants’ personal endorsements of African American stereotypes and contact with African Americans.5 There is also the possibility that “unconsciously acting on a stereotype” breaks down so that on tasks involving time-forced errors, like the shooter-bias video game, bias correlates positively with level of contact, while on tasks that leave time for conscious deliberation, like the rating of job applications, bias would correlate negatively with level of contact.6 This could be checked by decreasing the amount of time each participant had with each application to see if time-forced biases resulted.

It does seem clear that, at least in people’s imaginations, unfavorable trait ascriptions are difficult to shed, and that this probably applies both to individuals and to groups. The complexities of that process remain to be investigated, or have, perhaps, been investigated in work by Rothbart and Park (and others) since their 1986 paper. It also remains how Rothbart and Park’s findings relate to others’ such at Correll and colleagues’ (2002): Just how deep does changing one’s mind about a stereotype go? Under what circumstances will changing one’s mind about the truth of a stereotype produce a change in behavior? Are some behaviors immune to influence by such a mind change? If so, what processes will affect these behaviors?

 

References

Aronson, E., Wilson, T. D., & Akert, R. M. (2007). Social psychology. Upper Saddle River, NJ: Pearson Education.

Correll, J., Park, B., Judd, C. M., & Wittenbrink, B. (2002). The Police Officer’s Dilemma: Using ethnicity to disambiguate potentially threatening individuals. Journal of Personality and Social Psychology, 83, 1314-1329.

Rothbart, M., & Park, B. (1986). On the confirmability and disconfirmability of trait concepts.Journal of Personality and Social Psychology, 50, 131-142.

 

Very good, tight paper, with lots of interesting questions and thoughts that might be pursued. This is just about the epitome of what I’m looking for in a reaction paper – strong evidence of critical thinking, application of constructs across domains, integration of disparate material, and demonstration of knowledge that you probably would not have had before taking this course. 50/50

 

Btw, may I have permission to post this paper as an example of a great reaction paper for future classes? J

 

1 Awk., rephrase.

2 Strange use of this word; I might rephrase.

3 This last sentence is hard to parse…I’d rephrase. Also, did Correll et al. show that Ps thought AAs were more likely to have a gun, or were they just more likely to shoot even when a gun wasn’t present?

4 Good point.

5 This would address the first part: whether contact reduces personal bias and/or belief in the cultural ST – but how would this relate to further automatic application of the same ST?.

6 An interesting idea, but in a non-salient domain, do you think you would see effects? I guess the question is: how much does knowledge of cultural ST or endorsement of ST relate across domains – such as “blacks are poor workers” with “blacks are more likely to have a gun.”