Method

Participants. The sample consisted of 130 participants (79 female; 51 male). Most of them were students at the University of Jena, Germany. The mean age of the sample was 24.00 years (SD= 5.46). Recruitment took place through university mailing lists, advertisements on Facebook, and at the university campus. Two participants were excluded from the analysis; the first due to experiencing technical problems during the experiment, and the second for having already participated in a similar study. Participants were payed 5 Euros for their participation.

Materials. Photographs of faces were employed to grant each target a distinct identity. The images were derived from available databases (Ebner, Riediger, & Lindenberger, 2010; Langner, Dotsch, Bijlstra, Wigboldus, Hawk, & van Knippenberg, 2010; Lundqvist, Flykt, & Öhman, 1998; Minear & Park, 2004; PICS, 2008). Each picture consisted of a frontal facial shot with a neutral expression, presented in color with dimensions of 300x400 pixels. To prevent own-age or race-related biases from influencing target recognition (Hugenberg et al., 2010; Wiese, Komes, & Schweinberger, 2013), all of the photographs were of young Caucasian faces. Similarly, we attempted to prevent potential own-sex recognition biases (Herlitz & Lovén, 2013), by designing the experimental procedure so that female participants saw only female targets, and males only male targets.

In order to rule out potential memory effects due to the targets’ facial appearance, we conducted a pre-test. 49 participants (29 female) who did not participate in the main study evaluated 295 photographs for likability, trustworthiness and distinctiveness on a six-point scale (1= not at all; 6= very much). On the basis of these ratings, we selected 80 photographs of each sex to be utilized in the main study. Selections were made based on how close the ratings were to the scale midpoints on all three dimensions. Overall, the mean likability of

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target faces was 3.22 (SD= .55), the mean trustworthiness was 3.35 (SD= .49), and the mean distinctiveness was 3.28 (SD= .30).

A second pre-test with 100 student (64 female; 36 male) participants provided the basis for the behavior manipulation. Participants rated the 50-50 distribution of monetary units as being fair (1= unfair; 7= fair; M= 6.50, SD= 1.11), whereas taking 90 out of 100 units was classified as unfair (M= 1.3, SD= .75). The fairness ratings of the distributions clearly differed from each other, t(99)= 34.30; p< .01; d= 3.48. Hence, distributions between 45 to 55 out of 100 units presented the manipulation of “cooperative behavior”, and 5 to 15 units the manipulation of “uncooperative behavior” in the main study.

Procedure. The study began with participants providing informed consent for their participation. The experimenter asked if she could take a photograph of them with a neutral facial expression, allegedly for use in upcoming studies. However, the real purpose of this request was to make the target photographs employed in the study appear more realistic. After taking the photo, the experimenter accompanied participants to one of ten cubicles, for individual computer-based testing. Participants were asked to follow the instructions presented to them on the computer’s screen, commencing the first proper phase of the experiment. Participants read that scientific studies had found a relationship between personality and social behavior, and that the goal of the current experiment was to investigate this topic. They were then asked to complete a perceptual task, and learned that they were either ‘figure’ or ‘ground’ perceivers (e.g., Otten & Wentura, 1999). The perceptual types (i.e., minimal group memberships) were randomly assigned, together with the colors yellow and blue to represent ingroup and outgroup. The salience of group membership was enhanced using an open question about the new group, and t-shirts in group colors that were given to the participants. A short addendum stated that there was a close connection between perceptual type and social behavior, suggesting that there were fundamental psychological differences between the categories (e.g., Forgas & Fiedler, 1996). We did not specify the sizes of either group.

Moving to the second stage of the experiment, participants read the rules of the dictator game they would soon be asked to play. One of the two players involved (i.e., the target) would decide how much of 100 monetary units to keep, and how much to transfer to an ingroup member. The instructions lead the participants to believe that they were viewing decisions made by other participants, and that some of them were currently working in the other cubicles. We also claimed that participants would execute a team task with other

ingroup members after the experiment. In order to preserve their anonymity, every player would be assigned a random photograph as a personal avatar. In four preliminary rounds, participants decided how much of the 100 monetary units they would donate to another ingroup member. In the subsequent encoding phase, participants sequentially observed 40 target decisions (i.e., resource distributions in the dictator game). Photographs of faces (with a short introduction; e.g., “This is T.”) and indications of group membership (background color) were presented for 2 seconds before the target’s distributional decision appeared underneath. After another 4.5 seconds, the photograph and the decision disappeared, and participants were asked to rate the target’s fairness (e.g., “How fair do you think T. is?”) and state whether the target was associated with the ingroup or the outgroup. The next trial started after the questions were answered, continuing until all 40 decisions were observed. The order of faces was randomized between subjects, as was their behavior and group membership. Of the 40 targets viewed by each participant, 20 targets were ingroup members, of whom half donated 45 to 55 units (cooperation) and the other half 5 to 15 units (uncooperativeness). The other 20 targets were outgroup members, of whom half distributed fairly and half unfairly.

Once the encoding phase was completed, participants were allowed a short break before the final, testing phase began. In a surprise memory test, participants were shown the 40 faces they had previously seen, plus 40 new faces. Of the new faces, half were ingroup members and half outgroup members. Participants were asked to state whether they had seen each target before (old-new discrimination). If they indicated that they recognized a target, participants were asked to recall whether the target’s decision during the dictator game was fair or unfair (reputational memory).

Finally, participants answered items assessing ingroup identification and group impression and completed a manipulation check. Ingroup identification was accessed through four basic items on a seven-point scale (1= not at all; 7= very much): “I feel like a figure/ground perceiver”, “I am a figure/ground perceiver”, “I see myself as a figure/ground perceiver”, “I identify with figure/ground perceivers”. Participants were thanked, debriefed and given their incentives.7

Design. The study consisted of a 2 (target: ingroup vs outgroup) x 2 (behavior: cooperative vs uncooperative) design with two within-subject factors. More precisely, each

7 _{Additionally, a set of personality tests (right wing authoritarianism, victim justice sensitivity, social value}

orientation) was completed by all participants in order to control for individual differences. These variables did not influence the results, and are subsequently not included in this dissertation.

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participant was confronted with the four target types during the dictator game. Four dependent variables were analyzed via ANOVA: the perception of fairness of the targets’ behavior during the encoding phase (fairness), correct discrimination of previously seen ‘old’ faces as old in the test phase (hits), false discrimination of new faces as old (false alarms), correct discrimination of old faces as old including false alarms (recognition sensitivity; Pr), and

correct classification of target behavior as either cooperative or uncooperative (correct behavior classification). We applied Greenhouse-Geisser corrections in case of violations of sphericity, which could lead to fractional degrees of freedom. Furthermore, multinomial modeling of source monitoring provided estimates of reputational memory (elsewhere source memory, see Bayen et al., 1996; Buchner et al., 2009). The sample size was estimated from prior studies on reputational memory for uncooperative individuals (e.g., Bell, Buchner, Kroneisen, et al., 2012; Bell et al., 2010). The sample of 128 participants, conducting 80 trials each (N = 10,400), provided the possibility of detecting small differences between two parameters (df = 1; ω ≈ 0.04) with α= .05 and 1-β= .95 (calculated in G*Power; Faul, Erdfelder, Lang, & Buchner, 2007). We used Multitree for multinomial tree modeling (Moshagen, 2010).