Dataset for research paper: Effects of Racial Bias on Composite Construction
datasetposted on 27.05.2020 by Kavya Bhardwaj, Graham Hole
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Data for paper published in Applied Cognitive Psychology March 2020
We presented participants with a racially-ambiguous face and biased them into thinking it was Indian or British. These participants then constructed a facial composite, using E-Fit6. The composites were rated by separate groups of participants for racial appearance (Indian or European) and degree of resemblance to the target face.
Constructors and raters were European, overseas Indian or Indians living in India.
The datafile contains the raw data for this study: ratings of the ambiguous face's apparent race, the ratings of the composites' apparent race, and the ratings of the composites' resemblance to the target face.
We investigated how prior bias about a face's racial characteristics can affect its encoding and resultant facial composite construction. In total, 61 participant (24 Europeans, 18 Indians living in India and 19 Indians living in Europe) saw a racially ambiguous unfamiliar face and were led to believe it was either European or Indian. They created a composite of this face, using EFIT6. Two groups of independent raters (one Indian, the other European) then assessed the apparent race of each composite. A different two groups (one Indian, one European) assessed each composite's degree of resemblance to the target face, to determine whether this was influenced by the constructors' initial categorisation of the target face as “own-race” or “otherrace.” Composites appeared significantly more “Asian” or “European” according to the bias induced in their creators, but there was no evidence of any own-race bias in the resemblance ratings for the composites.