1. Note that this was a hybrid research talk + quick mini meta workshop.
If you need more detailed mini meta workshop materials, see my OSF page for the UMass Amherst Workshop or see the Resources for Mini Metas & Other Things document

2. The Personality Correlates of Sexism: Self vs. Others’ Perception
Jin X. Goh
Northeastern University

3. We interact with members of the opposite gender on a daily basis
We interact with members of the opposite gender on a daily basis. Mixed-gender interactions are very common and they can happen between family members, friends, romantic partners, and even enemies.

4. social interactions and perceptions?
How does sexism shape
social interactions and perceptions?
Given how common these interactions are, my research broadly examines how sexism plays a role in shaping social interactions and perceptions made during these interactions.

5. How to define sexism? People love women (Eagly & Mladinic, 1989)
Women are wonderful effect
Women are underrepresented throughout
Political sphere (Dahlerup, 2013)
STEM (Moss-Racusin et al., 2012)
Social & personality psych (Brown & Goh, 2016)
But first, how should we define sexism? Defining sexism may be more difficult than one may imagine given that research has consistently shown that people love women. Men and women both hold very positive attitudes towards women on both explicit and implicit level. This finding is so robust, it has been dubbed the Women are Wonderful Effect.
Nonetheless, women are often underrepresented in many key areas of society such as in the political sphere. Experimental field work by Corinne Moss-Racusin has found that women were less likely than men to be selected for a job in the STEM fields despite having the same qualification. My own work has show that although men and women are represented in equal numbers in social and personality psychology, women compared to men had fewer first author publications in JPSP and PSPB, their articles in these journals were less likely to be cited, and they were less likely to receive prestigious research awards.
So how do we reconcile these instances of divergent attitude and treatment of women?

6. Sexism toward Women Hostile Sexism (HS) Benevolent Sexism (BS)
Sexist antipathy
Belief that women are overthrowing men’s power
Through feminism or sexuality
Subjectively positive
Women are wonderful and pure but weak
Need to be protected & cherished
Well it depends on how you define sexism. According to Glick and Fiske, there are 2 forms of sexism. Hostile sexism or HS is what we normally associate sexism to be. It is sexist antipathy and the belief that women are trying to overthrow men’s power in society through feminism or sexuality.
--On the other hand, benevolent sexism or BS is a subjectively positive view of women as wonderful and pure yet weak. It is the assumption that women need to be protected and cherished by men. Simply put, it is chivalry.
--Hostile and Benevolent Sexism are not opposing construct. In fact, they are positively correlated. Additionally, women also hold these attitudes regarding their own gender.
(Glick & Fiske, 1996)

7. Ambivalent Sexism Inventory (ASI)
Examples of HS items:
“Women exaggerate problems they have at work”
“Most women interpret innocent remarks or acts as being sexist”
Examples of BS items:
“Women should be cherished and protected by men”
“Women, compared to men, tend to have a superior moral sensibility”
Hostile and benevolent sexism are measured through the ambivalent sexism inventory. An example of hostile sexism item is “women exaggerate problems they have at work.” An example of benevolent sexism item is “women should be cherished and protected by men.”
(Glick & Fiske, 1996)

8. Sexism & Gender Inequality
Hostile and benevolent sexism work together to maintain the status quo of gender inequality. Hostile sexism asserts men’s social dominance through degradation and defamation of women. As a result, hostile sexism often incurs resistance and it is therefore less likely to be accepted by women.

9. Sexism & Gender Inequality
BS increases support for status quo which then decreases interest in change (Becker & Wright, 2011)
Benevolent sexism, in contrast, asserts male dominance through paternalistic affection. Because of its friendly façade, women are less likely to resist sexism in such a form. Indeed, research has shown that exposing women to benevolent sexist statements as opposed to hostile sexist statements actually increases women’s support for status quo of gender inequality which then decreases their interest in promoting social change.

10. Sexism & Gender Roles
Higher men’s HS, less favorable toward nontraditional women
(career women)
In a study by Glick and colleagues, they found that men’s hostile sexism was negatively associated with attitudes towards women in nontraditional roles such as career women. That is, hostile sexist men liked nontraditional women less. Men’s benevolent sexism, in contrast, was associated with more favorable attitudes towards women in traditional roles, such as housewives. While hostile sexism punishes nontraditional roles, benevolent sexism celebrates and endorses traditional roles. In this instance, we can see that the two forms of sexism enforce gender inequality and men’s power in society in different but complementary ways.
More men’s BS, more favorable toward traditional women (housewives)
(Glick et al., 1997)

11. Sexism & Likeability BS men more likeable than HS men
People don’t see BS as sexism
Chivalry = good
If benevolent sexism is so bad, then why do we still endorse it as a society? In general, benevolent sexist men are perceived to be more likeable than hostile sexist men. This is probably because people don’t really see benevolent sexism as sexism. And in many societies, particularly western society, being chivalrous is viewed as a desirable behavior.
(Good & Rudman, 2010; Kilianski & Rudman, 1998)

12. Sexism & Behavior Mixed-gender dyads interacted in lab
Nonverbal & verbal behavior
Men w/ higher HS looked less friendly, smiled less
Men w/ higher BS looked friendlier, smiled more
In a similar vein, my previous research examined how hostile and benevolent sexist men behaved nonverbally and verbally when interacting with women they had just met in the lab. We found that men’s hostile sexism predicted less friendly behaviors and fewer smiles. In contrast, men’s benevolent sexism predicted friendlier behaviors and more smiles. In terms of nonverbal and verbal behaviors, benevolent sexist men actually did appear to be more likeable.
(Goh & Hall, 2015)

13. = Benevolent Sexism Polite? Agreeable? Civil? Kind? Nice?
Given benevolent sexism’s friendly façade, it is unsurprising that people endorse benevolent sexism and perceive it as a desirable and positive trait. However, it is important for us to distinguish these constructs. Is benevolent sexism simply being nice, kind, civil, polite, or in personality term, is benevolent sexism the same as or at least similar to agreeableness?

14. Individual Differences in Sexism
Meta-analysis between Big 5 & prejudice
Agreeableness: r = -.22
Extraversion: r = -.07
Neuroticism: r = .01
Openness: r = -.29
Conscientiousness: r = .00
In a meta-analysis that Sibley and Duckitt conducted in 2008, they looked at the correlation between big 5 traits and prejudice. They found that agreeableness and openness were both strongly and negatively associated with prejudice.
(Sibley & Duckitt, 2008)

15. Individual Differences in Sexism
Meta-analysis between Big 5 & prejudice
Only 25 studies on Big 5 & prejudice
5 on sexism specifically
Did not differentiate between HS & BS
However, in that meta-analysis, they found 25 studies and only 5 were on sexism specifically. And none differentiated between hostile and benevolent sexism. Given the lack of research in this area, my collaborator and I decided to conduct research examining individual differences in endorsement of hostile and benevolent sexism.
(Sibley & Duckitt, 2008)

16. Today’s Talk Personality and individual differences in HS & BS
Are benevolent sexists actually nice, agreeable people?
How do correlates differ between HS vs. BS?
How do friends perceive people w/ more HS or BS?
My research talk today will focus on the personality correlates of hostile and benevolent sexism
Importantly, I will try to distinguish benevolent sexism from interpersonal traits such as agreeableness.
I will also discuss how these personality correlates differ between hostile and benevolent sexism.
And I am excited to talk about a study we just finished on how friends perceive people with more hostile and benevolent sexism.

17. Today’s Talk 3 studies Part 1 Part 2
Study 1: college students’ self-report
Study 2: online community’s self-report
Study 3: college students’ self-report + friends’ report
I will talk about 3 studies my collaborator and I ran. All three studies use self-reports from college and online populations and Study 3 additionally recruited friends of participants to make more personality ratings.
I will divide the rest of this talk into 2 parts. In the first part, I will talk about the self-reports results and provide a brief overview on how to conduct a mini meta-analysis.
In the second part, I will contrast self report data with friends’ reports in Study 3 to demonstrate how sexism could potentially influence impression formation within one’s social network.
Part 1
Mini metas of self-reports & overview of mini metas
Part 2
Study 3: contrasting self vs. friends’ reports

18. Studies 1 to 3: Personality Self-Reports of Sexism
Part 1

19. Methods Study 1: N = 83 college students
60.2% women; M age = 19.3
Study 2: N = 179 Mechanical Turk workers
63.4% women; M age = 36.8
Study 3: N = 100 college students
55% women; M age = 18.9
We ran 3 studies. Studies 1 and 3 were conducted with student participants, and Study 2 was conducted online through Mturk.

20. Methods Shortened ASI (all 3 studies)
6-item HS scale and 6-item BS scale
HS: “When women lose to men in a fair competition, they typically complain about being discriminated against.”
BS: “In a disaster, women ought not necessarily to be rescued before men” (reverse)
In all 3 studies, we used a shorted version of the ambivalent sexism inventory. An example of hostile sexism item is “when women lose to men in a fair competition, they typically complain about being discriminated against.”
An example of benevolent sexism item is “in a disaster, women ought not necessarily to be rescued before men.” This item is reversed in scoring.

21. Methods Two dimensions of personality traits Communal traits
Relation to others
Concerns for others
Other-oriented
Agentic traits
Self-promotion
Concerns for self
Self-oriented
To capture the personality correlates of sexism, we focused on two dimensions: Communal and agentic traits. These two dimensions are sometimes referred to as the Big 2 traits of personality.
Communal traits are those that place the self in relation to others. They are generally other-oriented.
Agentic traits are about self-promotion. Typically, these traits are self-oriented.

22. Methods Communal traits Agreeableness (3 studies)
“I try to be courteous to everyone I meet”
Communal values (2 studies)
Politeness, equality, harmony, forgiveness
Ryff Positive Relations with Others (2 studies)
“Most people see me as loving and affectionate”
Humanitarianism-Egalitarianism (2 studies)
“One should be kind to all people”
We used four different scales to capture communal traits broadly. The first is agreeableness that we measured in all three studies. An example item is I try to be courteous to everyone I meet. The second is communal values and participants rated how important communal values such as politeness and equality are to them. Another scale we used was the Ryff Positive Relations with Others with an example item “Most people see me as loving and affectionate.” Finally, we asked participants to complete the humanitarianism-egalitarianism scale. An example is one should be kind to all people.

23. Methods Agentic traits Agentic values (2 studies)
Wealth, influence, competence, achievement
Narcissism (3 studies)
“Everyone likes to hear my stories”
Machiavellianism (2 studies)
“It is wise to flatter important people”
As for agentic traits, we first asked participants how important they think agentic values such as wealth and achievement are to them. We also included narcissism. An example is “everyone likes to hear my stories.” Finally we asked participants to complete a questionnaire on Machiavellianism and an example is “It is wise to flatter important people”

24. Mini Metas Similar methods across all 3 studies
Meta-analysis to summarize the results
Because all these studies used the same scales and the methods are the same, I meta-analyzed the results rather than presenting results from each study separatelys.
A meta-analysis can be easily done with a handful of studies, and I have an article on how to do this.
A mini meta is the same thing as a regular meta-analysis. I came up with the name mini meta simply to highlight the fact that you can do meta-analysis with only a handful of studies, and not just on hundreds of studies that we normally see in Psychological Bulletin.

25. Mini Metas Open Science Framework https://osf.io/6tfh5/
The article comes with an Excel template that I’ll show you later. You can go to my Open Science Framework to get the article, Excel, and other resources such as PowerPoints including this one. I believe Michelle sent out the link.
You can also find it on my website, our lab website, or my contacting me via and twitter.
[wait/ drink water]

26. Mini Metas: Why? Summarize several studies in one paper (bottom line)
No need to hide null or conflicting results
Calculate power or sample size for future studies
More power than individual studies/ uncover small effects
Editors or reviewers want it
So why should you do a mini meta-analysis? Well, there are many reasons and here are just some. For the studies that I am presenting today, these two points are particularly relevant. With 3 studies, we can summarize them all and get at the bottom line instead of trying to figure out what each study is saying separately or trying to find a pattern through 3 studies. Furthermore, there is no need to hide null or conflicting results. As you’ll see soon, some of my results were not in the direction I predicted as I’m sure many of you know from first hand experience.
Other reasons include calculating power or sample size for future studies.
By combining studies, you also have more statistical power than any study alone
And with more power, you can uncover small effects which is typical in our field.
Or the most practical reason, editors and reviewers increasingly want to see mini metas.
And believe me, mini meta is not hard to do!

27. Mini Metas: 10 Steps Decide on your research question
Determine the characteristics of your effect size (ES)
Find/ convert your ES
Calculate weighted mean ES (meta-analytic ES)
Understand your ES
Stouffer’s Z test
Random effects approach
Heterogeneity test
Contrast analysis
Report your meta-analysis
In the mini meta article, I outlined 10 steps. 1-10…
But for the purpose of this talk, only the first six steps are relevant.

28. Mini Metas: Step 1 Decide on your research question
Is benevolent sexism related to agreeableness?
Correlation in each study
Positive = more BS, more agreeable
Negative = more BS, less agreeable
In the first step, you need to decide on your research question and the direction of the effect.
As a demonstration, I will use this question: “Is benevolent sexism related to agreeableness?”
You have to then specify the direction of your effect size.
In all three studies, we used correlations, which is an effect size in case you didn’t know.
Positive correlation simply means more benevolent sexism, more agreeableness
Negative correlation means more benevolent sexism, less agreeableness

29. Mini Metas: Step 2 Determine the characteristics of effect size (ES)
Independence
Participants cannot be repeated in different ES
Figure out the N in each study
Study 1 (first ES): 83
Study 2 (second ES): 179
Study 3 (third ES): 100
Step 2 is determining the characteristics of your effect size.
Make sure that you maintain independence in all your effect sizes, meaning you cannot have the same participants in different effect sizes in the same meta-analysis.
Otherwise, determining the characteristics is easy. You just need to know the number of participants in each study.

30. Mini Metas: Step 3 Find/ convert your ES
2 families: Cohen’s d and Pearson correlation
Convertible from one to other
Easier to do meta-analysis using correlation
Correlation
No need to do anything else
Next we need to find or convert our effect size.
There are 2 general families of effect size. Cohen’s d which is typically used in t tests and Pearson correlation.
These two types of effect size are convertible from one to the other, and it is a lot easier to do meta-analysis using correlation if you don’t have a special software.
And because in my studies, I only used correlation, I don’t need to do anything else.

31. Mini Metas: Step 3 Agreeableness HS BS Study 1 -.19+ -.20+ Study 2
-.41***
-.02
Study 3
-.26**
.22*
Here are the data for each of the study between each sexism type and agreeableness.
As you can see in the middle column for the correlation between hostile sexism and agreeableness, the correlations are all in the negative direction but one is marginally significant.
But for benevolent sexism here, the results are not consistent. Study 1 is negative and marginal, study 2 has no relationship, and Study 3 is positive and significant.
So now we need to figure out what happens if we meta-analyze all 3 studies. and that may give us a better picture.
Noting that we do the meta-analysis separately for Hostile sexism and Benevolent sexism.
Meta-analytic r ?? ??
All controlling for gender and the other form of sexism.
+ p < .10. * p < .05. ** p < .01. *** p < .001.

32. Mini Metas: Step 4 Calculate weighted mean ES
This is your meta-analytic, overall ES
Weight by sample size (fixed-effect approach)
Fisher’s z transform correlations (rz) for normalization
Then convert back to regular r for presentation
To do that, we need to calculate the weighted mean effect size, which is your meta-analytic, overall result across all 3 studies.
By weighting, I just mean weighting by sample size so bigger studies count more assuming they reflect the true population better than smaller studies.
I don’t want to go into too much details, but this weighting method is a fixed-effect approach where you assume there’s one true effect in all your studies and variations in the studies are just due to sampling errors.
This is explained in more detail in the article but it’s too much for this talk, so look at the article if you have more concerns.
To calculate the weighted mean with your correlation, you first need to do what is known as the Fisher’s z transformation, marked by this sub z, which is just a step to normalize your distribution.
Importantly, you will need to convert the result back to regular pearson correlation when presenting your results in the paper.
The formula for weighted mean is pretty simple. The only things you need are the N for each study or each effect size, and the fisher’s z transformed correlation.
So let’s see how we do that in Excel.
𝑤𝑒𝑖𝑔ℎ𝑡𝑒𝑑 𝑟 𝑧 = ( 𝑁−3 𝑟 𝑧 ) (𝑁 −3)
Go to Excel

33. Mini Metas: Step 4 Agreeableness HS BS Study 1 -.19+ -.20+ Study 2
-.41***
-.02
Study 3
-.26**
.22*
Meta-analytic r
-.32
.00
When we meta-analyze all three studies, we get a negative correlation of .32 between hostile sexism and agreeableness. The more hostile sexist someone is, the less agreeable the person is.
As for benevolent sexism, meta-analyzing all three studies showed us that there is no relationship whatsoever between agreeableness and benevolent sexism.
All controlling for gender and the other form of sexism.
+ p < .10. * p < .05. ** p < .01. *** p < .001.

34. Mini Metas: Step 5 Understand your ES Small effects are very common
Convention (small, medium, large)
r = ±.10, r = ±.30, r = ±.50
Small effects are very common
Judge in relation to ES in similar studies/ other meta-analysis
Alright, now we need to try to understand what this effect size means.
The convention is that we categorize effect size as small, medium, and large.
For correlations, the convention for small is .1, medium is .3, and large is .5.
So our hostile sexism result was in the medium range.
I just want to point out that people are disappointed when their results don’t have a large magnitude but it is actually very common to get small effects in our field. I think the typical correlation is about .30.
It is more important to judge your effect size in relation to effect size in similar studies or other meta-analysis.
Conventional benchmark is useful but contextualizing your result to the literature is more important.

35. Mini Metas: Step 6 Stouffer’s Z test Summary p-value
Find the Z corresponding to each p-value (attach sign)
Then
𝑍 =𝑟 𝑁
Now onto the last step for today, you may want to find a corresponding p value attached to your effect size.
I personally am just happy to report an effect size but people are still obsessed with p values so this is useful.
The simplest and easiest method is known as the Stouffer’s Z test, which is basically finding the Z score for each of the p value or you can convert it from your correlation in each study then adding all of the Zs and divided that by the square root of K. K being the number of studies or number of effect sizes.
Z here is not your fisher’s z transformation, which is lower case. This is the Z we all learn in the beginning of stats class.
Let’s do this in Excel.
𝑍 𝑐𝑜𝑚𝑏𝑖𝑛𝑒𝑑 = 𝑍 𝑘
Go to Excel

36. Mini Metas: Step 6 Agreeableness HS BS Study 1 -.19+ -.20+ Study 2
-.41***
-.02
Study 3
-.26**
.22*
Meta-analytic r
-.32***
.00
We see that for hostile sexism, the relationship is significant at less than The test for benevolent sexism, unsurprisingly, is not significant.
And that’s how you do a quick simple mini meta analysis. I know this is a very simple and quick demonstration, but you can read more about it in my article or just contact me.
It really isn’t that hard to be honest. We’re basically just averaging numbers, and I hope you feel confident in doing one in the future!
All controlling for gender and the other form of sexism.
+ p < .10. * p < .05. ** p < .01. *** p < .001.

37. Part 1 Results Positive correlation between HS & BS
Mean r = .34, Stouffer’s Z = 6.54, p < .001, two-tailed
Always controlled for the other form of sexism
Also controlled for gender
Lose power if separate by gender (not enough N)
No gender differences
For the rest of Part 1, I will only present the meta-analytic self-report data.
Hostile and benevolent sexism correlated significantly in all three studies and the mean effect size correlation is .34 and significant.
So we controlled for the other form of sexism at all times due to this positive relationship.
Additionally, we opted to control for gender because we lose power if we separate the analysis by gender due to small sample size when separating by gender.
But just looking at the patterns, I can tell you that there are no visible gender differences. I can talk more about this after the talk if anyone is curious.

38. Results: Communal TraitsHS BS
Agreeableness
Communal values
Positive relations
Humanitarianism
-.32***
.00
-.14+
.18**
-.19**
.15*
Alright first lets take a look at the meta-analytic correlations between hostile sexism and communal traits.
Overall across these 4 traits we measured, it is obvious that there is a consistent negative relationship throughout.
As for benevolent sexism, the pattern is less obvious.
First as shown before, agreeableness and benevolent sexism had no relationship.
Interestingly, communal values and positive relations with others correlated positively with benevolent sexism.
Finally, humanitarianism did not correlate with benevolent sexism.
-.41***
.02
All controlling for gender and the other form of sexism.
+ p < .10. * p < .05. ** p < .01. *** p < .001.

39. Results: Agentic TraitsHS BS
Agentic values
Narcissism
Machiavellianism
.15**
.27***
.19***
.22***
.19**
.00
As for agentic traits, hostile sexism again demonstrated a very consistent patterns but this time they are all positive and significant.
For benevolent sexism, being more benevolent sexist is associated with valuing agency more and being more narcissistic.
It did not correlate with Machiavellianism though.
All controlling for gender and the other form of sexism.
+ p < .10. * p < .05. ** p < .01. *** p < .001.

40. Results: SimilaritiesHS BS
Agreeableness
-.32***
.00
Communal values
-.14+
.18**
Positive relations
-.19**
.15*
Humanitarianism
-.41***
.02
Agentic values
.15**
.27***
Narcissism
.19***
.22***
Machiavellianism
.19**
Next, to examine if there is any overall similarities in the personality profiles between hostile and benevolent sexism, I lined up the results here for all the traits. Using the meta-analytic results for hostile sexism here and benevolent sexism here, I can correlate the two forms of sexism to see the overall similarities in personality traits.
This method is known as vector correlation.
Overall, the personality profiles of the two forms of sexism correlated pretty strongly but it was not significant. This is not entirely surprising given that we only had 7 traits to work with.
In the paper my collaborator and I submitted on this, we actually had a few more traits I didn’t talk about here, and this relationship was significant and much stronger in magnitude, in the .6 range.
r = .49 ns

41. Summary HS negatively correlates w/ Communal Traits
HS people less concerned about others
HS positively correlates w/ Agentic Traits
HS people more concerned about themselves
Just to summarize part 1, we found that hostile sexism was negatively associated with communal traits in that hostile sexists are less concerned about others.
And they are also more agentic and more concerned about themselves.

42. Summary BS shows mixed relationships w/ Communal Traits
But no relationship w/ agreeableness
To care and cherish women require some communalism
Restricted to women, not all humanity
BS positively correlates w/ Agentic Traits
BS people more concerned about themselves
As for benevolent sexism, the overall patterns are more complicated.
First, there is no relationship between being benevolent sexist and being nice or agreeable, suggest that they are in fact different constructs.
Second, benevolent sexism showed positive correlation with communal values and positive relations with others. If you think about it, in order to care and cherish women, you do in fact need a degree of communalism.
Nonetheless, it is important to stress that benevolent sexism, however friendly helpful or communal it may seem, still assumes that women are inferior and weaker than men.
Benevolent sexism, like hostile sexism, also showed positive relationships with agentic traits suggesting that benevolent sexists are also very concerned about themselves.

43. Summary
Some similarities in overall personality profiles between HS and BS
Positive correlations between HS and BS
BS tapping into very similar personality structure as HS
Suggesting BS is indeed sexism, not a “nice personality”
Finally, there is also some similarities in the overall personality profiles between hostile and benevolent sexism.
After all, the two forms of sexism do correlate significantly and positively.
Benevolent sexism may be tapping into similar personality structure as hostile sexism
Suggesting that benevolent sexism is indeed a form of sexism and not just a confound or a similar construct to an agreeable personality trait.

44. Study 3: Self vs. Friends’ Perception of Sexism
Part 2
Alright let’s move onto the next part.

45. Study 3 Informant reports Informant reports vs. self-reports
Strangers, friends, family members, etc
Informant reports vs. self-reports
Narcissistic people perceive themselves more positively than their friends’ perception (Park & Colvin, 2014)
Do self-reports differ from friends’ perception?
Perhaps you weren’t all that convinced by my self-report data and that’s totally ok. I think one of the reasons why prejudice researchers seldom look at individual differences is this distrust of self-report, and for good reasons.
But this is something personality psychologists are aware of as well, and they often use what’s called informant reports. Which is just collecting perceptions and ratings about the participants from strangers, friends, or family members.
-This strategy is useful because informant reports can differ greatly from self-reports.
-for instance, narcissistic people think very highly of themselves, but their friends don’t perceive them as such
-So in this second part, I will talk about how self-report data can differ from friends’ perception on the big 5 personality traits.

46. Study 3: Method 100 participants (55% female) Shortened ASI
6-item HS scale and 6-item BS scale
Big 5 Traits
California Adult Q-Sort (Block, 1990)
As mentioned before in part 1, 100 participants came and completed the ambivalent sexism inventory. To measure the Big 5 traits, we used the Q-sort. Q-sort is not exactly the most common measure of personality so I will go into a bit details on how it works.

47. Personality or Behavioral description
Study 3: Method 5 8 12 16 18 16 12 8 5
Most uncharacteristic
Most characteristic
Each participant is given a deck of 100 cards, and each card has a personality or behavioral description.
Participants have to sort the 100 cards into 9 piles, ranging from what they think are most uncharacteristic to most characteristics of them.
They also need to sort the cards such that there are less cards at the tail ends and more in the middle, resembling a quasi-normal distribution.
Personality or Behavioral description
100 cards

48. “Is dependable and responsible”
Study 3: Method
Most uncharacteristic
Most characteristic
So for example, the first card is about being responsible. I think I’m a very responsible person so I will sort the card in the right most pile.
“Is dependable and responsible”
100 cards

49. “Is a talkative person”
Study 3: Method
Most uncharacteristic
Most characteristic
For the second card, I don’t think I’m all that talkative so ill put it in the uncharacteristic side.
“Is a talkative person”
99 cards

50. “Has a wide range of interests”
Study 3: Method
Most uncharacteristic
Most characteristic
Alright finally, I don’t think I have that wide of interests so I’ll just put it on the uncharacteristic side again.
“Has a wide range of interests”
98 cards

51. Study 3: Method 1 2 3 4 5 6 7 8 9 Most uncharacteristic
Most characteristic
Cards are given scores on a 1 to 9 rating scale. with the least uncharacteristic cards each receiving a score of 1 and the most characteristic cards receiving each receiving a score of 9.

52. Study 3: Method California Adult Q-Sort: CAQ (Block, 1990)
Certain cards reflect Big 5 qualities
Agreeableness
Extraversion
Neuroticism
Openness to experience
Conscientiousness
Add up “agreeableness cards”
Certain cards in the pile reflect the Big 5 traits, and to measure agreeableness in a person for example, you just add up the scores for the agreeableness-type cards based on the sorting scores described earlier.

53. Study 3: Method
Contact info for 3 close friends
Average of 2.3 friends for each participant
Average of 4.6 years of friendship
Q-sort of how they perceive participants
5-point scale, online
Averaged across friends to form one score for each participant
At the end of the study, participants gave us contact information for 3 close friends. In our data, each participant had data from average of 2.3 friends, and they’ve been friends for roughly 4 to 5 years on average.
These friends were ed and asked to complete the Q-sort online. Instead of sorting, they rated the participants on each item using a 5-point scale.
We then average across friends to form 1 score for each participant.
It is important to note that these friends were not told that we were interested in sexism as not to influence them. They were simply asked to make personality ratings of the participants.

54. Study 3: Results (HS) Big 5 Self-report Friends’ report Agreeableness
Extraversion
Neuroticism
Openness
Conscientiousness
For the results, I will separate the data for self report and friends’ report in different columns. And each row represents one of the Big 5 traits.

55. Study 3: Results Participants’ self-report Friends’ report
Own Big 5
Correlate w/ own HS or BS
Friends’ report
Friends’ perception of participants’ Big 5
Correlate w/ participants’ HS or BS self-report
All controlled for gender and the other sexism
For self-report, we correlated participants’ big 5 traits on the Q-sort with their own hostile or benevolent sexism scores.
As for the friends’ report, we correlated friends’ perception of the participants’ personality with the participants’ sexism scores.
In all analyses, we always controlled for gender and the other sexism like before.

56. Study 3: Results (HS) Big 5 Self-report Friends’ report Agreeableness
Extraversion
r = .07
r = -.03
Neuroticism
r = -.02
Openness
r = -.22*
r = -.12
Conscientiousness
r = -.11
r = -.15
Here are the data for hostile sexism
* p < .05. ** p < .01.

57. Study 3: Results (HS) Big 5 Self-report Friends’ report Agreeableness
Openness
r = -.22*
r = -.12
Now let’s take out the boring, non-significant, or no-relation data. First, participants with more hostile sexism are less agreeable as presented earlier in part of the mini meta, and their friends agree.
For openness to experience, participants with more hostile sexism are less opened. Friends’ report is in the same direction but not significant.
* p < .05. ** p < .01.

58. Study 3: Results (BS) Big 5 Self-report Friends’ report Agreeableness
Extraversion
Neuroticism
Openness
Conscientiousness
r = .22*
r = .03
r = .04
r = -.19+
r = -.09
r = .25*
For benevolent sexism, the data are more interesting in my opinion.
First, self-report of benevolent sexism and agreeableness was positively associated as presented in part of the mini meta earlier. However, friends’ perception did not have any relationship at all.
Benevolent sexism did not correlate with extraversion, but friends perceive participants with more benevolent sexism as less extraverted and more neurotic.
Openness was in the negative direction but not significant for both reports.
And finally, conscientiousness did not correlate significantly for self-report, but friends perceive participants with higher benevolent sexism as marginally less conscientious.
r = -.04
r = -.14
r = .12
r = -.17+
+ p < .10. * p < .05.

59. Study 3: Summary Self-reports match friends’ reports for HS
HS negatively correlates with Agreeableness and Openness to Experience
Same as meta-analysis on prejudice (Sibley & Duckitt, 2008)
Friends’ reports agree-ish…
All in same direction
So to summarize this second part, we found that hostile sexism is again easier to explain and more consistent.
Hostile sexism negatively correlates with agreeableness and openness to experience, and this pattern resembles the meta-analysis on big 5 and prejudice that Sibley and Duckitt conducted.
In general, friends’ reports agree with the self-report and the correlations are in the same directions.

60. Study 3: Summary Self-reports don’t match friends’ reports for BS
Even if participants think they are agreeable, their friends didn’t
Friends’ perceptions of participants with more BS were fairly negative
Less extraverted
More neurotic
Less conscientious
Study 3 also showed that self-reports don’t always correspond with friends’ perception for benevolent sexist individuals.
Even though participants reported themselves as being more agreeable, their friends did not.
Friends’ perceptions of benevolent sexist participants also tend to be more negative than self-report.
Friends perceived benevolent sexists as less extraverted, more neurotic, and less conscientious.

61. Conclusion

62. Take Home Points Benevolent Sexism ≠ Agreeableness
More similarities than differences in personality profiles of HS and BS
Friends’ reports don’t match up with benevolent sexists’ self-reports (but match hostile sexists’)
I know I’ve talked a lot and threw a lot of information at you. So here are just some take home points that I hope you will remember when you walk away from this talk.
First, benevolent sexism is not the same thing as agreeableness. Even if benevolent sexists are being nice, this is superficial and extended to women only.
Second, there are more similarities than differences in the personality profiles of hostile and benevolent sexism, but it is important to measure both forms of sexism.
Third, Friends’ reports don’t match up with self-reports for benevolent sexism. Friendship offers a very unique perspective into prejudice and intergroup dynamics, and I think this method deserves more attention.

63. Take Home Points Mini metas are useful and easy to do
Self-reports are useful but complement it with other methods (e.g., behavior, informant report)
Social AND personality psychology
In terms of research practice more broadly, I hope that you can see how useful and easy mini metas are.
I personally think self-reports are useful but it’s better to complement it with other methods such as behavioral expressions and informant report.
And finally, I think we need to connect social and personality psychology more intricately. The two fields don’t communicate as much as one might think. Methodological and statistical practices in another discipline can help us understand our research and intergroup relations better.

64. Acknowledgment Dr. Stefanie Tignor NEU Social Interaction Lab
Judith Hall, Katja Schlegel, Kazumi Ogawa, Kirsten Johnson, Michael Wang, and Vanessa Castro
Many incredible research assistants!!
On that note, I want to thank my collaborator Stefanie Tignor who did most of the work in Study 3. And I want to thank my lab and the many incredible research assistants who worked on these studies. Thank you!

65. Thank you! Questions?

66. Study 1: Descriptive Men’ HS Women’ HS Women’ BS Men’ BS M= 3.55 (.94)
Range= 1.33 – 5.33
Men’ BS
M= 3.72 (1.19)
Range= 1.33 – 6.17
Women’ HS
M= 3.55 (.94)
Range= 1.33 – 5.83
Women’ BS
M= 3.94 (.86)
Range= 1.83 – 5.67

67. Study 2: Descriptive Men’ HS Women’ HS Women’ BS Men’ BS
Range= 1.00 – 7.00
Men’ BS
M= 3.90 (1.36)
Range= 1.33 – 6.83
Women’ HS
M= 2.84 (1.17)
Range= 1.00 – 5.83
Women’ BS
M= 3.77 (1.27)
Range= 1.00 – 7.00

68. Study 3: Descriptive Men’ HS Women’ HS Women’ BS Men’ BS
Range= 1.17 – 5.50
Men’ BS
M= 3.96 (.88)
Range= 1.67 – 6.00
Women’ HS
M= 3.13 (1.17)
Range= 1.00 – 5.50
Women’ BS
M= 3.75 (.87)
Range= 1.67 – 6.00

69. Gender Differences in Self-Report Meta
Agreeableness HS BS
Men
-.41***
.12
Women
-.27***
-.08
All controlling for the other form of sexism.

70. Study 3: Results for MEN (HS)
Big 5
Self-report
Friends’ report
Agreeableness
-.38*
-.46**
Extraversion
-.13
-.11
Neuroticism
.25
.01
Openness
-.08
-.02
Conscientiousness
-.04

71. Study 3: Results for WOMEN (HS)
Big 5
Self-report
Friends’ report
Agreeableness
-.16
-.11
Extraversion
.26+
.05
Neuroticism
-.06
-.04
Openness
-.32*
-.20
Conscientiousness
-.17

72. Study 3: Results for MEN (BS)
Big 5
Self-report
Friends’ report
Agreeableness
.26+
.15
Extraversion
.06
-.17
Neuroticism
-.16
.22
Openness
-.28+
Conscientiousness
.09
-.23

73. Study 3: Results for WOMEN (BS)
Big 5
Self-report
Friends’ report
Agreeableness
.20
-.05
Extraversion
.04
-.20
Neuroticism
-.06
.28*
Openness
.16
-.12
Conscientiousness
.13