Social Consensus Feedback as a Strategy to Overcome Spontaneous Gender Stereotypes

Abstract

Across two experiments the present research examined the use of social-consensus feedback as a strategy for overcoming spontaneous gender stereotyping when certain social role nouns and professional terms are read. Participants were presented with word pairs comprising a role noun (e.g. surgeon) and a kinship term (e.g. mother), and asked to decide whether both terms could refer to the same person. In the absence of training, participants responded more slowly and less accurately to stereotype incongruent pairings (e.g. surgeon/mother) than stereotype congruent pairings (e.g. surgeon/father). When participants were provided with (fictitious) social consensus feedback, constructed so as to suggest that past participants did not succumb to stereotypes, performance to incongruent pairings improved significantly (Experiment 1). The mechanism(s) through which the social feedback operated were then investigated (Experiment 2), with results suggesting that success was owing to social compliance processes. Implications of findings for the field of discourse processing are discussed. OVERCOMING GENDER STEREOTYPES3 Considerable evidence suggests that readers often make gender inferences in text comprehension when explicit gender information is lacking (e.g. Carreiras, Garnham, Oakhill, & Cain, 1996; Duffy & Keir, 2004; Garnham, Oakhill, & Reynolds, 2002;Irmen, 2007;Kreiner, Sturt, & Garrod, 2008).Such inferences typically follow the use of social or occupational role nouns that have a strong gender bias, but that are not grammatically marked for gender e.g. the term beautician is strongly female-biased while the term builder is strongly male-biased. While grammatical gender languages can largely avoid gender stereotypic inferences by employing gender specific personal nouns to convey maleness and femaleness (e.g. le musician 'the [male] musician'/la musicienne 'the [female] musician' in French versus the musician in English), this is rarely possible in English. Instead, inferences based on stereotypical biases play an important role in building a cognitive representation of gender and, once established, are very difficult to overcome. This can result in processing difficulties when gender-related expectancies clash with explicitly stated gender information.Reynolds, Garnham and Oakhill (2006) gave participants a slightly adapted version of the now well known 'surgeon riddle' referenced by Sanford (1985). In this riddle, a father and son are involved in a car accident where the father dies but the son is taken to hospital for an operation.However, once there, the surgeon looks at the boy and exclaims "Oh my god, that is my son!" (Sanford, 1985: "I can't do this operation. This boy is my son."). When readers are asked how this can be, they typically infer that the surgeon is male and, despite knowing that the boy's father is dead, fail to override this inference so as to successfully conclude that the surgeon is the boy's mother. Indeed, Reynolds and colleagues report that 75% of readers who had not previously ...

Warm-hearted businessmen, competitive housewives? Effects of gender-fair language on adolescents’ perceptions of occupations

“…A full account of the impact of gender fair language on adolescents’ development of occupational gender stereotypes and their subsequent educational and vocational development could only be provided by longitudinal study designs. Although there is some evidence suggesting that repetitively combining role nouns with the non-stereotypical gender (e.g., surgeon/mother) indeed may have longer-term impact (e.g., Finnegan et al, 2015), longitudinal research on gender fair language does not exist at this time. Future research may want to explore this.…”

Counter-stereotypical pictures as a strategy for overcoming spontaneous gender stereotypes

“…This research has much in common with that of Finnegan et al (2015) who sought to overcome such occupational gender biases through the use of social-consensus feedback (again in conjunction with the judgment task of Oakhill et al, 2005 ). Finnegan et al (2015) administered three blocks of judgment trials with social consensus feedback provided after each response in Block 2 only.…”

“…This research has much in common with that of Finnegan et al (2015) who sought to overcome such occupational gender biases through the use of social-consensus feedback (again in conjunction with the judgment task of Oakhill et al, 2005 ). Finnegan et al (2015) administered three blocks of judgment trials with social consensus feedback provided after each response in Block 2 only. This feedback consisted of a sentence stating the percentage of previous students at the university who had completed the judgment task and agreed with the participant’s choice, e.g., ‘ _% of previous students agreed with you.’ In reality this feedback was fictitious and constructed so as to strongly and consistently suggest that past participants did not succumb to stereotype biases, i.e., that they accepted stereotype incongruent pairings without a problem.…”

“…This gender typicality plays an important role in building cognitive representations of gender and is the reason why people come to expect, for example, surgeons to be male and nurses to be female. It is now well established that such occupational stereotypes are activated spontaneously and unintentionally when certain gender-biased role nouns are read ( Carreiras et al, 1996 ; Garnham et al, 2002 , 2012 ; Kennison and Trofe, 2003 ; Duffy and Keir, 2004 ; Reynolds et al, 2006 ; Irmen, 2007 ; Kreiner et al, 2008 ; Finnegan et al, 2015 ), thus contributing to the maintenance and propagation of gender stereotypes in English speakers.…”

“…While Lai et al’s (2014) research was aimed at overcoming implicit racial biases (as opposed to the spontaneous gender biases that we are interested in), their findings are relevant here as stereotype reduction strategies have often proved successful across different domains. For instance, social norm information has been used to successfully reduce biases against groups such as racial minorities (e.g., Stangor et al, 2001 ), people suffering from obesity ( Puhl et al, 2005 ) and has also lowered levels of spontaneous gender stereotyping ( Finnegan et al, 2015 ).…”