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3.2: Module 7 – Gender Through a Cognitive Psychology Lens

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    Module 7: Gender Through a Cognitive Psychology Lens

    Module Overview

    In this module, we will learn about the actual and perceived differences in cognitive development and functioning in males and females. First, we will take a look at language and how languages impact gender, as well as how gender impacts the way in which we utilize language and communicate. Next, we will learn about cognitive differences between males and females. Are males really better at math than females? Well, we will see. Finally, we discuss how perceived differences may impact our performance.

    Module Outline

    • 7.1. Language
    • 7.2. Cognition

    Module Learning Outcomes

    • To become familiar with gendered versus nongender language
    • To understand how gender impacts communication and language patterns
    • To recognize the similarities and differences in cognitive development and abilities across gender
    • To begin to decipher real differences in abilities and perceived differences in abilities across gender
    • To gain an understanding of how perceived differences may impact stereotypes and how those stereotypes then impact performance.

    7.1. Language

    Section Learning Objectives

    • Gain foundational knowledge on the differences in how males and females communicate and use language
    • Understand gender versus nongendered language and their impacts

    7.1.1. Sex and Gender Differences in Language

    Language can impact many components of our lives. The words we choose, how we are spoken to, and the meaning that is attached to those experiences can completely make or break an experience. Have you ever noticed you have a different way of communicating than a friend or coworker? Have you ever noticed that you change your way of communicating based on who you are interacting with? You probably answered yes, and that is common. How about this – do you think that you change how you communicate depending on if you are talking to a male or female? What about your own gender – does that impact how you communicate? Let’s find out!

    Before we get started, lets discuss affiliative and assertive speech. Affiliative speech consists of a speech style in which an individual’s speech includes high levels of attempts to relate and support the listener/other individual. Assertive speech focuses on ensuring one’s needs/points/ are communicated to the listener/other individual. For example, someone using affiliative speech may say something like, “I understand why you are frustrated that you cannot attend the event. I would be frustrated, too.” whereas someone using assertive speech may say something such as, “It is not logical for you to attend the event. I need you here to manage the calls.”

    Women traditionally are generally stereotyped as more talkative, warmer, and more affiliative in their speech and men are stereotyped to be less talkative and more assertive and direct in their speech (Carli, 2017; Leaper & Ayres, 2007). However, research actually shows, although in childhood, girls talk more than boys (Carli, 2017; Leaper & Smith, 2004), in adulthood, men actually talk more than females (Leaper & Ayres, 2007)! In childhood, boys appear to use more assertive speech, whereas girls engage in more affiliative speech, but again, these differences are small (Carli, 2017; Leaper & Smith, 2004).

    The stereotype of women being more affiliative, and men more assertive, does have some evidence backing into adulthood (Leaper & Ayres, 2007). In general, women tend to disclose more about themselves and their personal lives to others. They offer more support in conversations, and search for areas of “relatedness.” Women also tend to be less direct in their communication (Carli, 2017). In contrast, men tend to be much more direct in their communication, offer more suggestions and corrections, and interrupt more frequently. However, women and men tend to show more affiliative interactions when they are interacting with women, than they do if they are interacting with men. More pleasant tones are used, more compliments are provided, and smiles offered, when interacting with women (Carli, 2017). So, it is not just our own sex that impacts our language, but also those who we are interacting with matters (Carli, 2017; Leaper & Ayers, 2007). For example, men are shown to evidence increased talking when they are with strangers or are in a group. Even more interesting, when we are with people we do not know, we are more likely to use more gender stereotypical language use (Leaper & Ayers, 2007). However, when we are discussing areas in which we feel we have an expertise, or are in a position of having more power, we engage in more assertive communication, despite our sex or gender.

    Although there are some sex differences in the way we communicate, men and women equally engage in providing cues of acknowledging that they are listening, giving directives, offering criticism, and presenting as agreeable. Moreover, when differences are noted between men and women, the differences found tend to be fairly small (Carli, 2017).

    What about nonverbal communication? The biggest differences between men and women appears to be the frequency in which one smiles (Carli, 2017). It seems women smile more than men (LaFrance, Hecht, & Paluck, 2003). The frequency in which one touches another person, when the other person is the opposite gender, while communicating is the same between men and women (Hall & Veccia, 1990). Essentially, women touch men and men touch women to a largely equal frequency when communicating. However, women will more frequently touch another woman while communicating than a man will touch another man.

    7.1.2. Gender Influences on Language

    Why is it that males and females tend to use language differently? One theory is explained by the social role theory. Social role theory outlines that the reason there are differences in the behavior of males and females is due to roles that each have within society. Essentially, societal structure influences the behaviors of individuals. A large component of society and societal structure is work and labor. Thus, labor division strongly dictates the behavior of men and women. Typically, labor of women is focused on domestic tasks and labor of men is focused more on work and tasks outside of the home. Social role theorists would explain that biology has a place within this theory because the physical makeup, influenced by biology, helped to define the labor roles. For example, men are bigger and stronger, physically, and thus, they were better able to do manual labor outside the home that required strength. Thus, this led to male roles being more focused to tasks outside of the home. Whereas women are able to bear children, and thus, biologically they are primed for domestic tasks and nurturing. However, as society has changed, the biological basis of the establishment of some of these roles has become less relevant; thus, in societies in which this is true, we see a decline in division of roles (Helgeson, 2012).

    So, what does that have to do with language? Well, because women’s roles have been focused on the home and nurturing, it fosters more communal and affiliative behaviors. Social role theory posits that the female role is primed to be agreeable, and to engage in more smiling, and nonverbal acknowledgement, all in efforts to build relationships. Adults are also more likely to command a girl to do something than a boy, thus, again, foster agentic behavior in boys and communal behavior in girls (Whiting & Edwards, 1988). Males fostered agentic may contribute to males using less attempts, through language, to attempt to foster relationships, and may partially explain their more assertive, direct communication patterns.

    7.1.3. Gendered Language

    He sat on the table – this is an example of language with gendered pronouns. There are actually three categories of language, as it relates to gender. There are gendered languages, natural gender languages, and genderless languages. Gendered languages are languages in which people, as well as objects, have a gender. These languages often assign a gender to non-living items. For example, in Spanish the word paper is masculine, and table is feminine. Examples of gendered languages are Spanish, Russian, German, and French. In gendered languages, gender is often “built into” the word which does not make adjusting the language for individuals that are transgender easy. Natural gender languages are language in which humans and animals are gendered, but non-human items and objects are not. English is an example of a natural gender language. Other examples include Norwegian and Swedish. Natural gender languages allow for additional pronouns such as ze/zir/zie/hir for individuals that do not identify as female or male, or prefer to be referred to with gender-neutral pronouns. Natural gender languages also allow for nonspecific pronouns such as “they” to avoid falsely gendering an individual as well. Unlike gendered languages, natural gender languages also can accommodate using words that do not require a pronoun such as student, partner, and employee, and avoids gendering all together. Genderless languages are languages in which no nouns are categorized. Examples of these languages include Chinese, Estonian, and Finnish.

    So how does gendered versus nongendered language impact us? Does it impact us at all? Are there differences in equality in countries in which the predominant language is genderless versus gendered? Actually, there are differences noted, but it may be different than what you would initially assume. Research does indicate that language that has grammatical gender within it can shape interactions and perceptions. These perceptions may then lead to changes in our judgement, decisions, behaviors, and ideas which then may change how one is treated and one’s status. Given this, one may assume that a country that has genderless language would have the most equality. This is actually not the case. What research has shown is, when gendered language (fully gendered, not natural gender language) is the predominant language, then there is less equality (e.g., considering economic factors despite controlling for any confounding factors such as governmental systems, religion, etc.) than natural gender and genderless language. However, natural gender language countries show higher equality than genderless language countries. Why is this? Well, research shows that gender neutral terms in genderless languages tend to be perceived with a male bias. Thus, genderless languages may actually lead to females missing opportunity to emphasize their role and visibility. Languages that allow for gender pronouns (natural gender languages) are hypothesized to promote more inclusion of women (Braun, 2001; Nissen, 2002). These languages also allow for gender-inclusive language, whereas gendered languages in which nearly everything is gendered are more difficult to implement neutral terms to promote gender inclusiveness (Prewitt-Freilino, Caswell, & Laakso, 2011).


    7.2. Cognition

    Section Learning Objectives

    • Obtain basic knowledge of how cognitive development differs between males and females.
    • Understand the differences in cognitive abilities between males and females.
    • Recognize the perceived differences in cognitive abilities between genders.
    • Learn about stereotype threats as it relates to gender and performance/outcomes.

    7.2.1. Sex Differences in Cognitive Development

    Cognitive development is the development of one’s intellectual ability to solve problems, reason, and learn. Intellectual ability is spread across several areas and domains, including, but not limited to: memory, language, logic reasoning, math reasoning, processing speed, etc. There are various theories on cognitive development. Some theorize that cognitive development happens in a continuous, but gradual, way whereas others hypothesize it develops in stages. Some theorize that there is one single trajectory path, whereas others hypothesize that there are multiple paths. Additionally, nativists theorize that cognition is largely influenced by nature (genes, biology) whereas environmentalists hypothesize that cognition is influenced more by nurture (Duffy, 2017).

    So, do males and females develop similarly in their intellectual development? Although society perceives many differences, research shows that while there are some differences, there are actually more similarities than differences. Moreover, the differences typically are not large, and by adulthood, many of the slight differences even out (Duffy, 2017).

    Let’s talk about the actual sex differences. Research indicates that, in childhood and continuing into adulthood, males’ brains are about 10% larger than females. This difference is maintained, even when researchers control for the fact that males, typically, are physically larger than females in all aspects. When going further into detail, studies have shown that the interstitial nuclei, which is largely responsible for sexual behavior, is larger and contains more cells in males than females. Interestingly, heterosexual men’s interstitial nuclei is larger than homosexual men’s. Another area of difference is with the amygdala. The amygdala is responsible for several functions, but the most prominent being emotion regulation and processing. In males, the amygdala grows during adolescence, but not in females,. This increase in size appears to persist, with research showing that even into adulthood, males have larger amygdala. Another area of structural difference is in the hippocampus. The hippocampus is largely responsible for memory. This area increases in females during adolescence, but does not show the same growth in males during adolescence. The caudate (an area in the basal ganglia responsible for procedural and associative learning as well as inhibitory control) is also larger in females (Grose-Fifer & diFilipo, 2017).

    7.2.2. Sex Differences in Cognitive Abilities

    7.2.2.1. Spatial abilities. Who performs better? Males are shown to perform better at a specific task – mental rotation. Mental rotation tasks are tasks in which an individual is shown variations of a stimuli that is rotated and must select the appropriate response. For an example, click here: https://www.psytoolkit.org/lessons/experiment_mentalrotation.html. Males tend to outperform females in mental rotation tasks, especially when there are timed elements of the task (e.g., limited time to respond; time pressures). Differences in spatial abilities can be seen in as young as 3 months old (Quinn & Liben, 2008). Research has also shown that females that have had a higher exposure to androgens do better on these spatial tasks than females that have not had increased androgen exposure. As such, there appears to be some biological bases. However, some environmental components cannot be ignored. For example, boy toys/interests (e.g., video games, building blocks) tend to focus in more on visual-spatial abilities compared to girl toys/interests (Grose-Fifer & diFilipo, 2017).

    How males and females solve problems, particularly mental rotation tasks, may vary. It appears that women tend to activate the frontal cortex area more whereas as males engage in a more automatic process. As such, females approach the tasks with a more analytical approach. Different areas of the brain being utilized, depending on sex, is found even when males and females perform similarly on a task. As such, even when males and females have similar abilities, how they solve problems may be different (Grose-Fifer & diFilipo, 2017).

    7.2.2.2. Verbal-based abilities. Females tend to outperform males in verbal fluency tasks. However, this difference is relatively small – smaller than the differences found in mental rotation tasks. There is not a found difference in the size of vocabulary between sexes; rather, it appears that girls have an increased ability to produce that vocabulary when a timed element is in play. Moreover, the advantage females have in verbal fluency early on begins to fade away around the age of six years old. (Grose-Fifer & diFilipo, 2017).

    Somewhat relatedly, males (children and adults) have poorer handwriting and struggle more to compose complex written language compared to females. Again, although males are not as quick and accurate in reading, their actual core reading capacity and abilities are equal to females (Berniger, Nielsen, Abbott, Wijsman, & Raskind, 2008).

    7.2.2.3. Math abilities. Abilities in mathematics do not appear to differ between males and females. Despite previous theories that have attempted to explain why males may have an advantage in mathematics, research simply fails to consistently support this. Males are not equipped with an innate advantage to outperform females in mathematics or science (Spelke, 2005). Although males tend to major in mathematics/sciences in college, and pursue more math-based careers, this does not seem to be due to a genuine cognitive advantage in this skillset. It is theorized that there may be more sociological reasons for this (as you will soon find out; Spelke, 2005).

    7.2.3. Stereotype Threat

    What if you were told before you went into a job interview, you were not at all qualified and would never get the job? What if you were told that most girls can’t get into STEM programs, just before you filled out your application for a STEM program (assuming you are a girl)? Do you think this would impact your performance on the interview or how you filled out your application? This is the idea of a stereotype threat. Essentially, a stereotype threat is when (1) a person is a member of the group being stereotyped, (2) in a situation in which the stereotype is relevant (a female taking a math test), and (3) the person is engaging in an activity that can be judged/evaluated (Betz, Ramsey, & Sekaquaptewa, 2014).

    Claude Steele is one of the main researchers in stereotype threat. He began his work in this area focusing on stereotype threat for African American and minority students in the university setting. He began to notice racial minorities and women underperformed academically, despite standardized testing that revealed these populations were capable of achieving equivalently to their white, male peers. He hypothesized that simply knowing about a stereotype (e.g., women aren’t as good at math, racial minorities are not high achieving, etc.) could hinder performance. In groundbreaking research, he revealed his hypothesis to be true (Steele & Aronson, 1995). In this study, Steel and Aronson (1995) conducted a series of mini-studies in which they manipulated the presence of a stereotype threat, the context of testing, etc. For example, one of their mini-studies consisted of having Black and White college students take a GRE. In one condition, the participants were told it would be diagnostic of their intellectual capacities whereas in another condition, participants were told the test was simply a problem-solving task that did not directly relate to intellectual ability. They conducted four different mini-studies that manipulated factors such as the ones described above. Some of the results of their study indicated that if Black participants were expecting a difficult, ability/diagnostic test, Black participants tended to be more aware of stereotypes, have increased concerns about their ability, show reluctance to have their racial identity somehow linked to performance, and even begin to make excuses for their performance. In general, the cumulation of findings from these mini-studies indicated that African American participants’ performance on standardized testing was negatively impacted (i.e., performed lower) when reminders of negative stereotypes of their abilities were strong. Likewise, when those conditions were removed, their standardized performance improved. Thus, their study provided significant support for stereotype threat (Steele & Aronson, 1995).

    Think about this, his research showed that it wasn’t that African American and other minority groups had a lower, innate ability (biology), and it wasn’t that they were less motivated, or that instructors were harsher toward them/their grading, it was knowledge about a stereotype about them regarding ability and performance that contributed to their lower performance (Betz, Ramsey, & Sekaquaptewa, 2014). Spencer, Steele and Quinn (1999) expanded this research from racial minorities to women, particularly as it relates to math performance. Similar to Steele and Aronson’s 1995 study, Spencer, Steele, and Quinn (1995) conducted several mini-studies to manipulate factors and presence of stereotype threat. For example, one of the studies consisted of administering GRE math problems. In one condition, participants were told that gender differences had been found in the test whereas in the other condition, participants were told that there had not been a gender difference found in the test. The overall results of the study showed that when women experienced stereotype threat, their performance was hindered (Spencer, Steele, & Quinn, 1999).

    This does not mean that someone believes they are actually worse at math, etc. It does not mean that they have internalized that stereotype and now believe it to be true about themselves. Not believing the stereotype, but being aware that others believe it, is enough to create a stereotype threat outcome (Huguet & Regner, 2007; Wheeler & Petty, 2001).

    7.2.3.1. Stereotype threat in school. As you may have gathered from the description of Spencer, Steele, and Quinn’s 1999 study, girls frequently experience stereotyped threats in school. It appears that around ages 7 to 8, gender stereotype awareness emerges (i.e., 5 to 7-year-old females were unaware, but 8 to 9-year-old females were aware whereas 5 to 7-year-old boys were aware of the stereotype regarding math abilities in girls; as cited in Galdi, Cadinu, & Tomasetto, 2014). Research has shown that females preform worse in math when under stereotype threat, but perform equivalently to males when the threat is removed. Stereotype threats have shown to reduce test performance, but these threats can also impact a female’s ability to incorporate and receive helpful feedback if they are overly focused and worried about providing confirmation of negative stereotypes. For example, if a female is overly worried about behavior or performing in such a way so as not to confirm a negative stereotype (e.g., women are bad in math), when someone, such as a teacher give constructive feedback or corrections, the female may be more reactive or defensive, and thus, unable to incorporate the helpful feedback that is being provided. When overly worried about confirming negative stereotypes, individuals may also pull away and avoid class discussions at school, etc. (Betz, Ramsey, & Sekaquaptewa, 2014).

    Gender stereotype threats may be more of an issue when a female’s identity is strongly rooted in being a female (versus their identity being strongly rooted in another area that is not negatively stereotyped). This is actually true for many stereotype threats, not just gender related threats. Essentially, if an individual sees their gender (or insert other negatively stereotyped group) as a major part of their identity, and the individual is highly focused on doing well in an area that is negatively stereotyped (for example, a female wanting to be an engineer), they may experience increased negative impacts from gender stereotype threats. This is even stronger when an individual strongly identifies with multiple groups that experience stereotype threats (e.g., a black woman; Bouche & Rydell, 2017).

    But why does the stereotype threat impact test performance? There are various theories, but one of the most commonly accepted is that by Toni Schmader. He theorized that when one is overly worried about a stereotype threat (e.g., reminded that because she belongs to the female group, she is likely to do poorly on the math test she is about to take), the worry ties up valuable cognitive resources. This worrying then impacts the capacity that one has to draw on their memory and to attend and focus on the task before them. As such, they are unable to utilize their abilities to their fullest and focus fully, impacting task performance. Research has shown that stereotype threats do not just impact test performance, it also impacts an individual’s ability to learn. This has been specifically shown to be true for females when learning perceptual tasks (Boucher, Rydell, Van Loo, & Rydell, 2012; Rydell, Shiffrin, Boucher, Van Loo, Rydell, 2010).

    However, some have argued against the actual validity of the idea of stereotype threats. Early on, a common argument was that most of these studies were conducted in labs and not natural settings, and thus, could not be generalized. Some researchers, such as Paul Sackett, believed that there would be a small effect in a natural setting. This began to spark an interest in conducing more natural setting studies. Naturalistic research has confirmed that stereotype threats indeed have negative impacts on academic experiences, performance, and career goals. Moreover, these negative impacts are accumulating.

    Other psychologists have argued that factors such as socialization, discrimination, and poverty stereotype threats do not explain everything. While these individuals are right, stereotype threats are found to be significant and important components. For example, when demographic surveys are moved from the beginning of an exam to the end of an exam, test performances were different. Specifically, researchers moved that moving a demographic study to the end of an AP calculus exam led to an increase in the number of female students that achieved exam scores high enough to receive college credit. This wasn’t small either – it increased to more than 47,000 females getting this passing score, per year (Stricker & Ward, 2004)!

    The above study is an example of what can be done to reduce the impacts of stereotype threats. Small logistical changes may have sizable impacts. Other strategies such as reframing tests as puzzles that need to be solved or framing critiques as opportunities for one to grow and learn may be helpful ways to reduce the impact of stereotype threats. Helping individuals learn to cope with concerns of stereotype threats and to use self-affirming statements may also be beneficial. Moreover, simply teaching individuals more about stereotype threat may be beneficial. Finally, having increased same-sex role models and higher rations of females represented in a class may be helpful (this is true for stereotype threats in general. For example, same-race role models and representation of same-race individuals may reduce race-related stereotype threat impacts; Boucher & Rydell, 2017).

    The number of cues in a class that remind an individual of a gender stereotype may be able to be reduce and lead to positive impacts. For example, as mentioned above, if there are few female classmates or teachers, increasing this can be helpful. Also, if patterns of who sits where or who is more frequently called upon is present, it may be helpful to reduce this. Additionally, if only one gender’s accomplishments are discussed or one gender’s interests are overly displayed in the classroom (e.g., classroom decorations strongly geared to males), efforts to reduce this could prove beneficial.


    Module Recap

    In this module, we learned about the actual and perceived differences in cognitive development and functioning in males and females. We gained knowledge about the differences in how men and women communicate. We also learned about how language impacts our understanding of gender and how our audience and status may impact how we communicate as well. We learned about differences in cognitive abilities between males and females. We discussed how there are very few differences in abilities, when truly looking at cognitive abilities. We also discussed how perceived differences impact the development of stereotypes that then lead to the presence of stereotype threats. We discovered how impactful these threats can be.


    3.2: Module 7 – Gender Through a Cognitive Psychology Lens is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.

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