One of the main advantages of measures of automatic cognition is supposed to be that they are less susceptible to faking than explicit tests. It is an empirical question, however, to what degree these measures can be faked, and the response might well differ for different measures. We tested whether the Implicit Association Test (IAT, Greenwald, McGhee, & Schwartz, 1998) cannot be faked as easily as explicit measures of the same constructs. We chose the Big-Five dimensions conscientiousness and extraversion as the constructs of interest. The results show, indeed, that the IAT is much less susceptible to faking than questionnaire measures are, even if no selective faking of single dimensions of the questionnaire occurred. However, given limited experience, scores on the IAT, too, are susceptible to faking.

Many models assume that habitual human behavior is guided by spontaneous, automatic, or implicit processes rather than by deliberate, rule-based, or explicit processes. Thus, math-ability self-concepts and math performance could be related to implicit math-gender stereotypes in addition to explicit stereotypes. Two studies assessed at what age implicit math-gender stereotyping can be observed and what the relations between these stereotypes and math-related outcomes are in children and adolescents. Implicit math-gender stereotypes could already be detected with Implicit Association Tests (Greenwald, McGhee, & Schwartz, 1998) among 9-year-old girls. Adolescent girls showed stronger implicit gender stereotypes than adolescent boys, who, on average, did not reveal implicit gender-stereotypic associations. Girls also already showed an implicit affinity to language versus math at 9 years of age. In a regression analysis, implicit math-gender stereotypes predicted academic self-concepts, academic achievement, and enrollment preferences above and beyond explicit math-gender stereotypes for girls but (with the exception of achievement) not for boys. These findings suggest implicit gender stereotypes are an important factor in the dropout of female students from math-intensive fields.

The categories that social targets belong to are often activated automatically. Most studies investigating social categorization have used visual stimuli or verbal labels, whereas ethnolinguistic identity theory posits that language is an essential dimension of ethnic identity. Language should therefore be used for social categorization. In 2 experiments, using the "Who Said What?" paradigm, the authors investigated social categorization by using accents (auditory stimuli) and looks (visual stimuli) to indicate ethnicity, either separately or in combination. Given either looks or accents only, the authors demonstrated that ethnic categorization can be based on accents, and the authors found a similar degree of ethnic categorization by accents and looks. When ethnic cues of looks and accents were combined by creating cross categories, there was a clear predominance of accents as meaningful cues for categorization, as shown in the respective parameters of a multinomial model. The present findings are discussed with regard to the generalizability of findings using one channel of presentation (e.g., visual) and the asymmetry found with different presentation channels for the category ethnicity.

Gender stereotype theory suggests that men are generally perceived as more masculine than women, whereas women are generally perceived as more feminine than men. Several scales have been developed to measure fundamental aspects of gender stereotypes (e.g., agency and communion, competence and warmth, or instrumentality and expressivity). Although omitted in later version, Bem's original Sex Role Inventory included the items “masculine” and “feminine” in addition to more specific gender-stereotypical attributes. We argue that it is useful to be able to measure these two core concepts in a reliable, valid, and parsimonious way. We introduce a new and brief scale, the Traditional Masculinity-Femininity (TMF) scale, designed to assess central facets of self-ascribed masculinity-femininity. Studies 1–2 used known-groups approaches (participants differing in gender and sexual orientation) to validate the scale and provide evidence of its convergent validity. As expected the TMF reliably measured a one-dimensional masculinity-femininity construct. Moreover, the TMF correlated moderately with other gender-related measures. Demonstrating incremental validity, the TMF predicted gender and sexual orientation in a superior way than established adjective-based measures. Furthermore, the TMF was connected to criterion characteristics, such as judgments as straight by laypersons for the whole sample, voice pitch characteristics for the female subsample, and contact to gay men for the male subsample, and outperformed other gender-related scales. Taken together, as long as gender differences continue to exist, we suggest that the TMF provides a valuable methodological addition for research into gender stereotypes.

Attitudes toward lesbians, gay men, bisexual women, and bisexual men were assessed in a national representative sample of 2,006 self-identified heterosexual women and men living in Germany. Replicating previous findings, younger people held more favorable attitudes than older people; women held more favorable attitudes than men; and men held more favorable attitudes toward female than male homosexuality, whereas women did not differentiate. However, women held more favorable attitudes toward homosexuals than toward bisexuals, whereas men did not differentiate. Knowing a homosexual person was an important predictor of attitudes, as was political party preference. Both same-sex and opposite-sex sexual attraction were substantially related with attitudes. Our findings support the notion that attitudes toward lesbians, gay men, bisexual women, and bisexual men are related but distinct constructs.

According to theories brought forward recently, implicit measures based on reaction times, for instance Implicit Association Tests (IATs), should predict spontaneous behavior better than explicit measures. We applied five IATs to the measurement of the Big Five personality factors and tested whether the IATs predicted spontaneous behavior. The results show that, although implicit and explicit measures of personality dimensions were related at times, the correlations between them and with behavior suggest that these constructs should be differentiated. IATs predicted spontaneous behavior, but explicit measures did not. In contrast, explicit measures, but not IATs, were related to transparent self-ratings of behavior.

Better retention of self-produced as opposed to experimenter-presented material is called generation effect; the reverse phenomenon is the negative generation effect. Both are found in intentional-learning experiments in which generating versus reading is manipulated between subjects. The present article presents an overview of those findings and aims at clarifying the conditions under which these effects emerge. Experiments 1 and 2 demonstrate that if cue-target relations are manipulated within one list, a negative generation effect in free recall can be obtained for all items, no matter which cue-target relation they bear. In Experiment 3, cue-target relations were manipulated between lists. Here, a negative generation effect in free recall was found only in lists in which items were cued with words that mismatched the inter-target relations, whereas a positive generation effect was observed in those lists in which the generation cues matched the inter-target relations. A subsequent cued-recall test demonstrated that in cases of mismatch of relations, participants in the generate condition process cue-target relations at the expense of inter-target relations. The three-factor theory can be integrated with the task-demand account in a transfer-appropriate processing framework to accommodate these findings.

We investigated implicit gender stereotypes related to math and language separately, using Go/No-go Association Tasks. Samples were grade 9 adolescents (N=187) and university students (N=189) in Germany. Research questions concerned the existence of and gender differences in implicit stereotypes. While typical explicit-stereotyping findings were replicated, implicit math-male stereotypes were found in male, but not in female participants. Females revealed strong language-female stereotypes, whereas males showed language-male counterstereotypes. Thus, females' implicit math-gender stereotypes were the only ones that did not link own gender to the respective academic domain in a selfserving way. Further, females' stronger stereotypes were related to lower and males' to higher scores on constructs related to math ability, corroborating implicit stereotypes' importance.