The Dads4Daughters test

Welcome to the Dads4Daughters Test: an implicit gender bias test developed by Split Second Research and Blinc. The test is designed to reveal both unconscious gender biases and hence encourage participants to compare them with their conscious attitudes towards the different genders.

Implicit association tests (of which the Harvard IAT and affective priming test are the two most famous) measure attitudes and beliefs that people find difficult to express or even know they have. For example, you might express the view that women are just as capable as men in the work place, but subconsciously you might feel more comfortable having a male boss. In general, you might consciously support gender equality, but subconsciously hold views about the sorts of activities, jobs, and roles that are exclusively male or female.

Using an affective priming approach, the test requires the participant to categorise gendered words (for instance ‘he’, ‘she’, ‘his, ‘hers’) to male or female. Using the response rates to this section as an indicator of the participants average response rates, the next two sections then introduce primer words (such as ‘leader’ or ‘decisive’) before, for instance, ‘his’ to see if the prime word affects that user’s response time to the original gendered word . If the response rate for ‘her’ when primed with ‘leader’ is longer than when ‘leader’ precedes ‘her’, then this could indicate the user more readily associates men with leadership roles and other such inferences.

In contrast, the Harvard IAT tells the participant which words are ‘male’ and ‘female’ for the purposes of the test and then asks them to categorise them into those two groups. In this case, ‘leader’ may be designated ‘male’ on the prescribed list and ‘assistant’ female. As such, the test can feel more like a memory exercise as opposed to eliciting to unconscious responses.

Based on the individual’s Dads4Daughters Test results, the participant then will be given a suggestions of constructive pledges they could take based on their most ‘biased’ area (from professions, roles, career fields or personal qualities).