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exp4_data_about.txt
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exp4_data_about.txt
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The Experiment 4 data (memory with journalism prompts) is structured as follows:
'data.frame': 8771 obs. of 13 variables:
$ Condition : Factor w/ 3 levels "first","last",..: 1 1 1 1 1 1 1 1 1 1 ...
Three between-subjects conditions: first name, last name, full name.
$ List : Factor w/ 9 levels "1A","1B","1C",..: 3 3 3 3 3 3 3 8 8 8 ...
9 lists to counterbalance which 7 of the 21 names participants saw, and the combinations
of names and prompts to balance possible gender associations of the prompts.
$ GenderRating: num 6.24 2.61 6.82 5.34 1.28 4.39 3.87 5.22 1.24 5.86 ...
Gender rating of the first names (from pilot data), with 1 as very masculine and
7 as very feminine.
$ Name : Factor w/ 63 levels "Ashley Cook",..: 1 18 21 22 25 28 50 5 7 15 ...
Name shown. In all conditions, the first instance of the name was a full name, then
the other three instances varied according to condition. There are 21 first names,
21 last names, and 3 combinations into full names.
$ Prompt : Factor w/ 7 levels "album","animals",..: 3 4 1 2 6 7 5 3 2 5 ...
7 story prompts.
$ Male : num 0 1 0 0 1 1 1 1 1 0 ...
1 if participant answered "male", 0 if not.
$ Female : num 1 0 1 1 0 0 0 0 0 1 ...
1 if participant answered "female", 0 if not.
$ Other : num 0 0 0 0 0 0 0 0 0 0 ...
1 if answer was something other than "male" or "female" (i.e. "I don't know", "I don't
remember"), 0 if not.
$ Likeable : int 2 1 3 2 4 3 3 3 2 4 ...
Rating of the character as likeable, with 1 as most and 7 as least.
$ Accomplished: int 1 2 1 4 2 2 2 5 3 3 ...
Rating of the character as accomplished, with 1 as most and 7 as least.
$ Important : int 2 1 5 5 1 4 3 3 2 2 ...
Rating of the character as important, with 1 as most and 7 as least.
$ SubjID : Factor w/ 1253 levels "Exp4_P1","Exp4_P10",..:
Participant ID.
$ SubjGenderMale: int 1 1 1 1 1 1 1 1 1 1 ...
Participants wrote their gender in a free-response box. NA values (N=91) are participants who did not
provide a gender, generally misreading the question and writing their age instead. This is the variable
used in the supplementary analysis, with male (N=602) and transgender male (N=1) participants coded as 1
and female (N=555), transgender female (N=1), and nonbinary (N=3) participants are coded as 0. The original
responses are not included in the public dataset, to preserve the privacy of gender minority participants.
Participant age, education level, and race/ethnicity were also collected but are not included in the
public dataset.