Report 3
Data Sources
The rating data are from the Psychological Science Accelerator project: To Which World Regions Does the Valence-Dominance Model of Social Perception Apply? (Jones et al. 2021).
The face stimuli are from Ma, Correll, and Wittenbrink (2015). While the original image set refers to “target self-identified race (A = asian; B = black; L = latinx; W = white)”, we have already renamed this variable to “Ethnicity” and refer to it as such throughout the report.
The 120 faces were rated on a 1-9 scale for 13 different characteristics: “aggressive”, “attractive”, “caring”, “confident”, “dominant”, “emostable”, “intelligent”, “mean”, “responsible”, “sociable”, “trustworthy”, “unhappy”, and “weird”. Data are presented for average ratings in each of 11 world regions.
Trust and Dominance
Factor analysis revealed two factors, labelled “valence” and “dominance”. Trustworthiness is often used as a single rating proxy for valence, and dominant for dominance.
Figure 1 shows the distribution of trustworthiness and dominance for each region.
UK Ratings
Table 1 shows the mean and standard deviation of trustworthiness and dominance ratings for the UK, broken down by gender of face.
Trustworthy | Dominant | |||
---|---|---|---|---|
Gender | mean | SD | mean | SD |
Female | 5.50 | 0.73 | 4.46 | 0.55 |
Male | 4.90 | 0.67 | 4.46 | 0.61 |
Original Insight
Create a plot (Figure 2) that shows the relationship between face age and trustworthiness / dominance ratings, separately for each gender. Filter data to show only data from one region (of your choice). Make sure to describe the plot clearly here and in a brief caption.
Reflections
Code Clarity and Efficiency
Thing I did
How it improves code clarity…
Thing I did
How it improves code efficiency…
Sources of Learning
Please explain the sources of learning you used in this assessment, including the book, help sessions, peers, online sources, and generative AI. (up to 300 words)