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Experiment 1 method and results

Experiment 1 method and results 5Nd1e
In Experiment 1, participants were assigned to one of the two arbitrary groups, saw repeated and non-repeated positive and negative stereotypical statements about their in-group and out-group, and evaluated stereotypical statements about both groups as “true” or “false”. We predicted that participants would rate repeated stereotypical statements about their in-group more frequently as “true” than any other stereotypical statements. Materials Dot Estimation Task. For minimal grouping purposes, we used Ratner and Amodio’s (2013) Numerical Estimation Style Test (NEST). NEST includes 3 practice and 10 test trials. Clusters of black dots (consisting of 98-200 identical dots) were presented in the white background followed by a number estimation question in each trial. Stereotypes. We selected traits from Anderson (1968) and translated these traits to Turkish. An English language expert checked Turkish versions of the traits. Three Turkish language experts rated the top 200 personality traits that have the highest meaningfulness score in the original study. These three experts agreed on 92 positive traits and 84 negative traits. Among those, for positive stereotypes, we selected the top 40 traits having the highest likeability rates, and for negative stereotypes, we selected 40 traits having the lowest likeability traits. For stereotypical sentences, we used a very simple sentence structure that is the combination of group names (over-estimators or under-estimators) and the traits. We chose to keep the sentences as simple as the real stereotypes about real groups for face validity. Identification Measures. We followed Cameron (2004) for identification measures by including three dimensions of social identity; centrality, in-group affect, and in-group ties. Therefore, we used a four-item measure (“I identify myself with other over-estimators/under-estimators”, “I see myself as an over-estimator/under-estimator”, “I am glad that I am an over-estimator/under-estimator”, “I have strong ties with other over-estimators/under-estimators”). We used a 7-point Likert scale for these items indicating 1= “totally agree” and 7= “totally disagree”. We also asked participants to choose the best option showing their relationship with their in-group on the Pictorial Item of Identity Fusion Scale (Swann et al. , 2009). Participants. 96 undergraduate students (73 female, 22 male, 1 unspecified; Mage= 21, SDage= 1. 47) from various departments at Duzce University and Abant Izzet Baysal University participated in the study. They participated either voluntarily or for course credit. Only one student was omitted from the data because s/he gave uniform answers showing that s/he did not pay attention to the task. Design. Participants were assigned to one of the two groups randomly (i. e. , “over-estimators” vs “under-estimators”). All participants evaluated stereotypes from eight categories in a 2x2x2 within-participants design: repetition (repeated vs. new), group (in-group vs. out-group), valence (positive vs. negative). Procedure. The participants took part individually in the experiment. The experimenter welcomed, read the consent form, made the participant sit in front of the computer and after taking the consent she began the experiment on SuperLab software. Participants took the experiment as follows; minimal group assignment, statement evaluation, and identification measurements with demographics. First, participants had three practice and ten test trials for the group assignment. In each trial, they saw dots for 5 s and we asked them to estimate how many dots they have seen without time limitation. Participants waited for 20 s by thinking that the program was calculating their results. A false feedback appeared on the computer screen saying “According to the numerical estimation test you are overestimator/underestimator”. Second, the statement exposure and evaluation phase started. At the beginning of the exposure phase, they were instructed to read 40 statements and try to remember them. They randomly saw statements from four categories (in-group positive, in-group negative, out-group positive, out-group negative). Each statement appeared for 2. 5 s and a fixation dot appeared for 1 s. After that, participants judged 20 new and 20 old statements from the above-mentioned four categories in a binary fashion (Unkelbach, 2007). After truth judgments, they evaluated the statements as “seen” or “not seen” in the first phase for manipulation check. Third, identification with the group was measured through 4 items and Pictorial Identity Diffusion Scale. After demographics and two political orientation questions, the experimenter provided the information that the grouping information was fake, debriefed the purpose of the experiment, and thanked participants. Results Truth Evaluations. We analysed means of truth ratings with a 2 (repetition: repeated vs non-repeated) X 2 (group: in-group ve out-group) X 2 (valence: positive vs negative) repeated measures ANOVA. Participants are more likely to evaluate repeated stereotypes (M = 0. 50, SD= 0. 18) as true compared to non-repeated stereotypes (M = 0. 36, SD= 0. 17), F (1, 94) = 48. 448, p<. 001, ηp² =. 340) as expected. In addition, ANOVA showed a main effect of valence. Participants are more likely to evaluate positive stereotypes (M =. 50, SD= 0. 20) as true compared to out-group stereotypes (M = 0. 36, SD= 0. 18), F (1, 94) = 32. 157, p<. 001, ηp² =. 255. Furthermore, participants are more likely to evaluate in-group stereotypes (M = 0. 46, SD= 0. 18) as true than out-group stereotypes (M = 0. 40, SD= 0. 17), F (1, 94) = 11. 030, p=. 001, ηp² =. 105. As ingroup favouritism suggests, The group effect was larger for positive statements compared to negative statements, F (1, 94) =28. 581, p<. 001, ηp² =. 233. Participants judged positive stereotypes (M = 0. 59, SD= 0. 28) as more true than negative stereotypes (M = 0. 33, SD= 0. 19) when the stereotype is about their in-group whereas they did not judge positive stereotypes (M = 0. 41, SD= 0. 25) as more true than negative stereotypes (M = 0. 40, SD= 0. 22) when the stereotype is about their out-group. There was no significant interaction of repetition, group, and valence, F (1, 94) =2. 087, p=. 152. Reaction Times. The measured reaction times were checked if they are at three standard deviations above or below the average of the participant’s reaction times. A 2 (repetition: repeated vs non-repeated) X 2 (group: in-group ve out-group) X 2 (valence: positive vs negative) ANOVA was used for analysis of the data. Results indicated that participants responded faster to in-group statements (M = 2770) than out-group statements (M = 2948), F(1, 94) =12, 189, p<. 05, ηp2 =. 114. In addition, participants responded slightly faster to positive statements (M = 2813) than negative statements (M = 2904), (F(1, 95) =3, 217, p=. 076). However, the effect of repetition was not significant (F(1, 94) =1, 093, p>. 05). Manipulation check. We checked whether participants could recognize repeated statements. A paired sample t-test showed participants responded to repeated statements ``Yes, I saw it” (M = 56%) more frequently than “No, I didn't see it” (M = 34%).
In
Experiment
1,
participants
were assigned
to one of the two arbitrary
groups
,
saw
repeated and non-repeated
positive
and
negative
stereotypical
statements
about their in-group and out-group, and evaluated
stereotypical
statements
about both
groups
as
“true”
or “false”. We predicted that
participants
would rate repeated
stereotypical
statements
about their in-group more
frequently
as
“true”
than any other
stereotypical
statements. Materials Dot
Estimation
Task. For minimal grouping purposes, we
used
Ratner
and
Amodio
’s (2013) Numerical
Estimation
Style
Test
(NEST). NEST includes 3 practice and 10
test
trials. Clusters of black dots (consisting of 98-200 identical dots)
were presented
in the white background followed by a number
estimation
question in each trial. Stereotypes. We selected
traits
from Anderson (1968) and translated these
traits
to Turkish. An English language expert
checked
Turkish versions of the
traits
. Three Turkish language experts rated the top 200 personality
traits
that have the highest meaningfulness score in the original study. These three experts
agreed
on 92
positive
traits
and 84
negative
traits
. Among those, for
positive
stereotypes
, we selected the top 40
traits
having the highest
likeability
rates, and for
negative
stereotypes
, we selected 40
traits
having the lowest
likeability
traits. For
stereotypical
sentences, we
used
a
very
simple sentence structure
that is
the combination of
group
names (over-estimators or under-estimators) and the
traits
. We chose to
keep
the sentences as simple as the real
stereotypes
about real
groups
for face validity. Identification
Measures
. We followed Cameron (2004) for identification
measures
by including three dimensions of social identity; centrality, in-group affect, and in-group ties.
Therefore
, we
used
a four-item
measure
(“I identify myself with other over-estimators/under-estimators”, “I
see
myself as an over-estimator/under-estimator”, “I am glad that I am an over-estimator/under-estimator”, “I have strong ties with other over-estimators/under-estimators”). We
used
a 7-point
Likert
scale for these items indicating 1= “
totally
agree
” and 7= “
totally
disagree”. We
also
asked
participants
to choose the best option showing their relationship with their in-group on the Pictorial Item of Identity Fusion Scale (
Swann et
al.
,
2009). Participants
. 96 undergraduate students (73 female, 22 male, 1 unspecified; Mage= 21,
SDage
= 1. 47) from various departments at
Duzce
University and
Abant
Izzet
Baysal
University participated in the study. They participated either
voluntarily
or for course credit.
Only
one student
was omitted
from the data
because
s/he gave uniform answers showing that s/he did not pay attention to the task. Design.
Participants
were assigned
to one of the two
groups
randomly
(
i. e.
,
“over-estimators” vs “under-estimators”). All
participants
evaluated
stereotypes
from eight categories in a
2x2
x2 within-participants design:
repetition
(repeated vs. new),
group
(in-group vs. out-group),
valence
(
positive
vs.
negative
). Procedure. The
participants
took part
individually
in the
experiment
. The experimenter welcomed, read the consent form, made the
participant
sit in front of the computer and after taking the consent she began the
experiment
on
SuperLab
software.
Participants
took the
experiment
as follows; minimal
group
assignment,
statement
evaluation, and identification measurements with demographics.
First
,
participants
had three practice and ten
test
trials for the
group
assignment. In each trial, they
saw
dots for 5
s and
we asked them to estimate how
many
dots they have
seen
without
time
limitation.
Participants
waited for 20 s by thinking that the program was calculating their results. A false feedback appeared on the computer screen saying “According to the numerical
estimation
test
you are
overestimator
/
underestimator
”. Second, the
statement
exposure and evaluation phase
started
. At the beginning of the exposure phase, they
were instructed
to read 40
statements
and try to remember them. They
randomly
saw
statements
from four categories (in-group
positive
, in-group
negative
, out-group
positive
, out-group
negative)
. Each
statement
appeared for 2. 5 s and a fixation
dot
appeared for 1 s. After that,
participants
judged 20 new and 20
old
statements
from the above-mentioned four categories
in a binary fashion
(
Unkelbach
, 2007). After truth judgments, they evaluated the
statements
as “
seen
” or “not
seen
” in the
first
phase for manipulation
check
. Third, identification with the
group
was measured
through 4 items and Pictorial Identity Diffusion Scale. After demographics and two political orientation questions, the experimenter provided the information that the grouping information was fake, debriefed the purpose of the
experiment
, and thanked participants. Results Truth Evaluations. We
analysed
means of truth ratings with a 2
(repetition
: repeated vs non-repeated) X 2
(group
: in-group ve out-group) X 2
(valence
:
positive
vs
negative)
repeated
measures
ANOVA.
Participants
are more likely to evaluate repeated
stereotypes
(M = 0. 50, SD= 0. 18) as
true
compared to non-repeated
stereotypes
(M = 0. 36, SD= 0. 17), F (1, 94) = 48. 448, p<. 001,
ηp²
=. 340
)
as
expected
.
In addition
, ANOVA
showed
a main effect of
valence
.
Participants
are more likely to evaluate
positive
stereotypes
(M =. 50, SD= 0. 20) as
true
compared to out-group
stereotypes
(M = 0. 36, SD= 0. 18), F (1, 94) = 32. 157, p<. 001,
ηp²
=. 255.
Furthermore
,
participants
are more likely to evaluate in-group
stereotypes
(M = 0. 46, SD= 0. 18) as
true
than
out-group
stereotypes
(M = 0. 40, SD= 0. 17), F (1, 94) = 11. 030, p=. 001,
ηp²
=. 105. As
ingroup
favouritism
suggests, The
group
effect was larger for
positive
statements
compared to
negative
statements
, F (1, 94) =28. 581, p<. 001,
ηp²
=. 233.
Participants
judged
positive
stereotypes
(M = 0. 59, SD= 0. 28) as more
true
than
negative
stereotypes
(M = 0. 33, SD= 0. 19) when the
stereotype
is about their in-group whereas they did not judge
positive
stereotypes
(M = 0. 41, SD= 0. 25) as more
true
than
negative
stereotypes
(M = 0. 40, SD= 0. 22) when the
stereotype
is about their out-group. There was no significant interaction of
repetition
,
group
, and
valence
, F (1, 94) =2. 087, p=. 152. Reaction
Times
. The measured reaction
times
were
checked
if they are at three standard deviations above or below the average of the
participant’s
reaction
times
. A 2
(repetition
: repeated vs non-repeated) X 2
(group
: in-group ve out-group) X 2
(valence
:
positive
vs
negative)
ANOVA was
used
for analysis of the data. Results indicated that
participants
responded faster to in-group
statements
(M = 2770) than out-group
statements
(M = 2948), F(1, 94) =12, 189, p<. 05, ηp2 =. 114.
In addition
,
participants
responded
slightly
faster to
positive
statements
(M = 2813) than
negative
statements
(M = 2904), (F(1, 95) =3, 217, p=. 076).
However
, the effect of
repetition
was not significant (F(1, 94) =1, 093, p>. 05). Manipulation
check
. We
checked
whether
participants
could recognize repeated
statements
. A paired sample t-
test
showed
participants
responded to repeated
statements
``
Yes, I
saw
it” (M = 56%) more
frequently
than “No, I didn't
see
it” (M = 34%).
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