Bias can be described as cognitive distortion effects that influence our perceptions, actions and behavior. These distortions affect assumptions, attitudes and stereotypes in an implicit, unconscious way, which is why the term implicit bias is usually used synonymously with unconscious bias. Implicit bias is thus the result of mental associations that we experience through direct and indirect communications. Implicit bias can lead to either positive or negative impacts. Implicit bias is similar to explicit bias, but unlike explicit bias, implicit bias does not necessarily agree with our conscious beliefs and reflected attitudes. Implicit bias, which is present in all humans, influences decision-making behavior as an unconscious and involuntary distortion effect and causes structural inequalities. Therefore, it is important to understand implicit bias in order to reduce social inequality and discrimination. A widely known online tool for checking one’s own bias is the Harvard implicit association test (IAT), which is not based on individual self-reports but uses a measurement method to record social attitudes.
The combination of implicit and explicit bias has been demonstrated in relevant studies by Mavda, among others. The background of this combination is both everyday experiences and moments of socialization of the de facto separation of different social groups as well as the abundance of stereotypical representations in the media. On top of that, personal experiences, values and attitudes can reduce or increase implicit bias. Explicit bias turns into implicit bias mainly through anti-prejudice upbringing. Implicit bias becomes explicit bias through the normalization of prejudices.
Gender bias refers to systematic bias effects that are characterized by gender-related stereotyping and prejudices and influence both perceptions and decisions. Gender bias is not only effective in everyday situations, in communication and decisions, but also in science and research, for example in relation to research design and results as well as personnel policy decisions. It thus shapes science and research despite supposedly objective performance and evaluation standards - despite the ethos of independent, gender-neutral research. Studies show that gender bias is present in search and promotion processes, funding and financing opportunities and teaching evaluations, among other things. These results are summarized in publications by EU research networks (e.g. LERU, ECU, STI Conference).
The papers refer to the connection between gender bias, racial bias and other bias as well as to the fundamental challenge of analyzing intersectional bias, which includes the consideration of several dimensions of inequality in their interdependence with the gender dimension. So far, few studies have performed an intersectional analysis in which gender bias and racial bias are looked at in their combination. However, the collection of essays titled “Presumed Incompetent. The Intersections of Race and Class for Women in Academia” published in 2012 has led to increased awareness in research on bias from an intersectional perspective and an increasing number of studies on women of color in academia.
The classic studies listed below take an intersectional research perspective:
The majority of these research results have originated in the USA and Great Britain, as well as in Scandinavia; studies are pending for the German-speaking area. Future studies within the German-speaking research landscape are faced with the challenge of dealing with the terms race and ethnicity used in previous studies. They have to take into account the social discourses and realities of life specific to the nation-state in the use of terms in order to achieve a reflected use of those terms (see ECU Use of language: race and ethnicity). Despite initial studies analyzing race and gender from an intersectional research perspective, the majority of bias research is limited to gender or race without analyzing their entanglement or including further dimensions of inequality.