This data object is more unusual than most. It is a list of 4 data
frames. The four data frames correspond to the data used in Studies 1-4 of
the referenced paper, and these data frames each have variables (columns)
that are among the following:
- subject
Subject ID. Note that Subject 1 in the first data frame
(data set) does not correspond to Subject 1 in the second data frame.
- gender
Gender of the subject.
- age
Age of the subject, in years.
- trait
The trait that the children were making a judgement about,
which was either nice or smart.
- target
The age group of the people the children were making judgements
about (as being either nice or smart): children or adults.
- stereotype
The proportion of trials where the child picked a gender
target that matched the trait that was the same as the gender of the child.
For example, suppose we had 18 pictures, where each picture showed 2 men and
2 women (and a different set of people in each photo). Then if we asked a
boy to pick the person in each picture who they believed to be really smart,
this stereotype variable would report the fraction of pictures where
the boy picked a man. When a girl reviews the photos, then this
stereotype variable reports the fraction of photos where she picked
a woman. That is, this variable differs in meaning depending on the gender
of the child. (This variable design is a little confusing, but it is useful
when analyzing the data.)
- high_achieve_caution
The proportion of trials where the child said
that children of their own gender were high-achieving in school.
- interest
Average score that measured the interest of the child in
the game.
- difference
A difference score between the interest of the child in
the “smart” game and their interest in the “try-hard” game.