From the original article on December 12, 2020. Author: Julius Branson.
It’s been said in the PUA reddit community TheRedPill that women are the “oldest 18 year old” in the house,” that is, that they have the mind of an 18 year old man. What does this mean? Others, such as Youtuber boogie2988 have claimed they have the “mind of a 14 year old.” How can this sentiment be quantified and tested? Consider a 12 year old: it’s commonly thought that people this age are, generally, deficient in cognitive abilities that are relevant to social standing and day to day life. These can be broken down into three (not necessarily completely distinct) categories that seem to cover the vast majority of cognitive differences: emotional maturity, or control over and adaptive value of emotions; judgment, or the ability to avoid bad decisions; and rationality, or the complexity of thought. Here, theRedPill’s claim about the minds of women will be investigated: how women compare to men in terms of emotional maturity, judgment ability, and rationality, and in turn how they compare to boys of different ages.
Let judgement be operationalized as “the ability to avoid harmful decisions.” There are then a number of subcomponents that can be identified that make it easier to recognize what kind of data might indicate differences in judgment. One is risk aversion, the extent to which risk taking is optimized. Too much risk, and you’re destroyed. Too little, and you’re dominated by competitors. The risk-taking component of judgment intuitively seems to be important in regards to financial decisions and investments. Further, the ability to make healthy long term decisions, such as whether or not to take a drug, or what field to start a career in, or how many children to have, is also probably influenced by risk taking. One task that neatly measures judgment, and risk taking in particular, is the Iowa Gambling Task, in which participants have to choose from a number of decks of varying risks and in which they are punished or rewarded accordingly. Women consistently underperform in comparison to men to the tune of d =~ 0.5 (Singh 2016)(Reavis & Overman 2001)(Bolla et al 2004)(Van den Bos et al 2013). In comparison, teenagers are disparaged because they perform the same as men, with the performance gap on the task being statistically insignificant and d < 0.1. However, 10-11 year old boys underperform men to the same degree as women, as d = 0.48 (Cauffman et al 2010).
Another measure that is adjacent to judgment and risk taking is known as selective attention or impulse control. “Examples of psychological measures of inhibitory control include the Stroop task, Simon task, Flanker task, antisaccade tasks, delay-of-gratification tasks, go/no-go tasks, and stop-signal tasks”. These are designed to measure the ability to “control one’s attention, behavior, thoughts, and/or emotions to override a strong internal predisposition or external lure, and instead do what’s more appropriate or needed” (Diamond 2013). However, not all tasks are created equal. The go/no-go task, for example, does not correlate with the Simon task, and it’s easy to see why. The go/go-no involves split-second motor accuracy in regards to a go or no-go signal. The Simon task, on the other hand, involves the ability to executively depress the tendency to get distracted by irrelevant stimuli when completing a task. The former might be said to measure the impulse-accuracy of the underbrain while the latter probably has more to do with executive function. Women score maturely on the go/no-go task and the similar stop-signal task. However, women underperform on the Simon task at d = 0.39 (Stoet 2017)(Merritt et al 2005) as they are more easily distracted and suffer greater performance losses after distraction. This is most similar to the gap between men and 13-15 year old boys (Couperus 2011). Narrowing it down, women can be estimated to perform equivalently to males of about 14 years on selective attention loaded tasks. The fact that women underperform on more complex tasks may reflect equal processing speed with men, as there is little to no IQ gap between the sexes. It would seem, however, that processing quality does have some differences.
Hedonism and emotional maturity also intersect with judgment and are further linked. The former is defined as susceptibility to momentary whims and may interact with influenceability in women. The latter is defined as general rigor of and control over emotions. Less control or less rigorous emotions may lead to more emotional decisions (states not involved in most lab tests), and higher rates of traumatization per incident. Hedonism and emotional maturity, likely not completely distinct concepts, plausibly both interact in susceptibility and severity to drug addiction, for instance. Of all the domains of cognition, children, at least older children, are in particular thought to be deficient in emotional maturity and to act more hedonistically and materialistically. They are thought to have less control over their feelings and to have more fragile and easily influenced emotional states compared to men. How do women hold up?
Women impulse buy much more than men per self report (Segal & Podoshen 2012), and roughly match the self reports of 14 year old boys on the same scale (Lin & Chen 2012). This is striking for two reasons: social acceptability of impulse between the two groups and differential financial pressures. If I had to bet, women are underreporting impulse buying more so than boys because it is seen as more irresponsible and negligent at older ages, in part because a lot of women are responsible for children and necessary costs, while most 14 year olds have mostly, if not totally, expendable income. 14 year old boys are probably in a better position to impulse buy and suffer from less embarrassment when reporting their behavior than women. The fact that these two groups report roughly the same rates of impulse buying is significant. Furthemore, less impulse control might lead to being more influenceable or vice versa. While they don’t report more dependence on material goods for happiness, women do report being more invested in vanity than men at d = .3 and in being more impacted by advertisements and friend’s consumption expectation at d = .4 (Keech et al 2019). Women similarly report being more self conscious at d = .3 (Keech et al 2019). Boys are similarly reported to be elevated in relation to men on scales of self consciousness and influenceability (Lin & Chen 2012) (Pechmann et al 2005) (Chaplin & John 2017), but the research in the advertising field is too poor and too averse to straight forward discussion of early vs. mid vs. late adolescent vs. adult effect sizes (because straightforward discussion reveals what has been shown here) for a male-age to be clearly assigned to women based on this data in particular. However, it is almost certainly between 12 and 15. Moving on, however, social anxiety and conformity data seems closely related to financial influenceability and self consciousness data. Women seem to differ from men in social anxiety at d = .3, suggesting it overlaps with self consciousness significantly. Furthermore, 20 year old women report in one study as much social anxiety as 10th grade boys (Puklek & Vidmar 2000). In another study, 15 or 16 year old women reported as much social anxiety as boys at their peak anxiety-age: 13 or 14 (Ranta et al 2007). The data is not perfect but it consistently suggests that grown women experience self consciousness at similar levels as young teen boys. Conformity data backs this up. A metaanalysis found women conform more than men at d = .3 (Hyde 1990). The data on conformity and age is not as nice as it could be, but in light of what has already been found it essentially replicates by elevated conformity scores of pubertal boys. In one study, 20 year old women conformed as much as 15 year old boys (Costanzo & Shaw 1966). Another study found elevations in conformity for males around 13-15 and reported that “girls have less behavioral independence from parents than boys” (Berndt 1979). Overall, women seem to impulse buy, conform, and experience self consciousness at rates elevated to men and most similar to boys in puberty who are 12-15 years old. These behaviors indicate underlying susceptibility to momentary whims (hedonism) and increased emotional dependency (meaning less independent control over emotions, i.e. emotional maturity). They also reflect and are reflected by deficiencies in selective attention and overall judgment. Furthermore, they may also reflect an overall lower complexity of thought (rationality) in women, compared to men, where it is hypothesized that women think more in black and white and are less inclined to think critically/independently.
Moving on, addiction, traumatization, and mental illness data also reflect differences in susceptibility to momentary whims and control and rigor of emotions. Children are often thought to be more mentally fragile, unable to handle trauma and suffering as well as adults. Furthermore, “adolescents” are frequently said to be at an elevated risk of addiction, leading to calls for high age restrictions (Pechmann et al 2005). Women, when compared to men, also show elevated susceptibility to addiction as well: “Women exhibit more rapid escalation from casual drug taking to addiction, exhibit a greater withdrawal response with abstinence, and tend to exhibit greater vulnerability than men in terms of treatment outcome” (Becker 2016). Another study reported that recovering female addicts crave their drug more than recovering men (Kennedy et al 2013). This is interesting because for some drugs, such as alcohol, there are more male abusers. The difference is possibly caused by differences in social pressures — men are more likely to have hard times and face less shame for bouts with drugs. Despite this difference in overall use, however, the female brain shows a similar susceptibility to drugs as found in kids, with addiction coming more easily and being harder to kick. It is difficult to quantify this tendency as to compare women directly to boys since most of the data is qualitative and there are serious social factors that influence overall drug usage rates in a population (but not addiction susceptibility after exposure). Furthermore it is considered unethical to administer addictive drugs in a lab to test addiction susceptibility. One study, however, replicated previous discussions by reporting “Unlike men, the initial use of heroin by women was highly influenced by a man [in women]” (Hser & McGlothlin 1987). Differences in addiction susceptibility between the sexes are almost certainly biological, relating to structural brain differences and hormones (Bobzean et al 2014). Suffice it to say that, in regards to addiction susceptibility, women most likely show similar susceptibility as pubescent males, owing to previous discussions.
Women are also more susceptible to traumatization (per incident) than men (Breslau & Anthony 2017). One study reported “Women were found to be at significantly increased risk for PTSD following exposure to serious trauma (odds ratio approximately 5), even when sexual trauma–which predominates in women–was excluded (odds ratio approximately 3)” (Stein et al 2000). This difference is extreme: 70 year old women (the least likely age group of women to have PTSD) are as likely to have PTSD as 13 year old boys, the latter being far more likely to be the victim of serious violent crime (Ditlevsen & Elklit 2010) (Perkins 1997). This indicates a serious gap in female and male emotional rigor and independent emotional control, consistent with previously reviewed data. Other mental illness data replicates this. Teenagers and women have about a 10% chance of being diagnosed with Major Depression in any given year, while men only have a 4% chance (Lieber 2020) (RAMH 2020). Women are also twice as likely as men to have an anxiety disorder (RAMH 2020). Depression and anxiety are doubtlessly intertwined with social factors, but nonetheless, the idea replicates. This all indicates that women are more emotionally fragile and likely to break down from stress than men, similarly (or worse) to boys of about 13 and under.
Judgment and emotional maturity have been thoroughly examined, leaving rationality, the complexity of thought. A subset of complexity of thought can be indicated by a person’s susceptibility to propaganda, as that indicates the extent to which they think critically, deeply, and independently. Women have already been shown to be roughly as susceptible to propaganda and advertising as 14 year old boys. Another well known difference between men and women relates to complexity of thought. Men are much more likely to be “systemizers”, systemizing being “the drive to analyse and explore a system, to extract underlying rules that govern the behaviour of a system; and the drive to construct systems” (The Guardian). Systemization increases with age in both sexes, making this deficit a neotenous trait (Auyeung et al 2012). If systemizing is the drive to analyse and think deeply, then other data will probably show that women as a group tend to think more in black and white. Borderline Personality Disorder data shows this: a symptom of it is black and white thinking, and 90% of patients are women (Daros et al 2013). Both this and systemizing data replicate the finding that women have lower complexity of thought, a trait thought to be common in children of quite young ages.
Overall, the data indicates that, relative to men, women roughly have the “mind of a 13 or 14 year old.” More generally, women tend to score on tasks related to cognitive functioning as pubescent boys do, whether that be children who have just started puberty (10-12) or boys in the midst of it (12-14). From about 15 onward, men outperform women, having reached their maturity after a longer time of development than women. Indeed, this result was anticipated by sex differences in puberty. Women reach adult physiology around 13 or 14, while men do the same around 15 or 16. Hence men have about 2 more years of development than women. 15 or 16 year old males consistently demonstrate equivalent cognitive capacities to older men. It is intuitive that, their development being “cut short”, women would forever demonstrate cognitive capacities similar to those of boys the age at which women stop maturing, 13 or 14. Furthermore, bodily neoteny anticipated the results: women look and sound more childish. Women are smaller, have less hair, more childish faces, have higher pitched voices, etc. Their physical strength is roughly equal to that of 12 or 13 year old boys. It is intuitive that behavior might mirror these traits, and here it’s been found that it does.
However, there are still uncertainties. For instance, it could be debated as to what causes the above-evidenced performance gaps. Tasks on which women outperform men could be discussed. Women tend to have an aversion to risk taking, despite it seeming that they are more impulsive. This could lead to greater judgment in some situations in which risk is intolerable. Furthermore, even if women have “younger” minds than men, experience and learning might play a role in behavior and make women more “mature” than pubescent boys in many ways. The policy implications of the findings here are open to these contention points and ethical considerations.
Singh, V. (2016). Sex-differences, handedness, and lateralization in the Iowa Gambling Task. Frontiers in psychology, 7, 708. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4885871/
Reavis, R., & Overman, W. H. (2001). Adult sex differences on a decision-making task previously shown to depend on the orbital prefrontal cortex. Behavioral Neuroscience, 115(1), 196–206. doi:10.1037/0735-7044.115.1.196 https://psycnet.apa.org/doiLanding?doi=10.1037%2F0735-7044.115.1.196
K.I. Bolla, D.A. Eldreth, J.A. Matochik, J.L. Cadet, Sex-related Differences in a Gambling Task and Its Neurological Correlates, Cerebral Cortex, Volume 14, Issue 11, November 2004, Pages 1226–1232, https://doi.org/10.1093/cercor/bhh083
Van den Bos, R., Homberg, J., & de Visser, L. (2013). A critical review of sex differences in decision-making tasks: Focus on the Iowa Gambling Task. Behavioural Brain Research, 238, 95–108. doi:10.1016/j.bbr.2012.10.002 https://www.sciencedirect.com/science/article/pii/S0166432812006419?via%3Dihub
Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., Banich, M. T., Graham, S., & Woolard, J. (2010). Age differences in affective decision making as indexed by performance on the Iowa Gambling Task. Developmental psychology, 46(1), 193. http://psych.colorado.edu/~mbanich/p/Cauffman2010_age_differences.pdf
Stoet, G. (2017). Sex differences in the Simon task help to interpret sex differences in selective attention. Psychological Research, 81, 571 – 581. https://www.semanticscholar.org/paper/Sex-differences-in-the-Simon-task-help-to-interpret-Stoet/31711e4006429777390d6fe5c79b67f6d6048991
Diamond, A. (2013). Executive functions. Annual review of psychology, 64, 135-168. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084861/
Merritt, P., Hirshman, E., Wharton, W., Devlin, J., Stangl, B., Bennett, S., & Hawkins, L. (2005). Gender differences in selective attention: Evidence from a spatial orienting task. Journal of Vision, 5(8), 1000-1000. https://jov.arvojournals.org/article.aspx?articleid=2131748
Couperus, J. W. (2011). Perceptual load influences selective attention across development. Developmental Psychology, 47(5), 1431. https://www.researchgate.net/publication/51234267_Perceptual_Load_Influences_Selective_Attention_Across_Development
Segal, B., & Podoshen, J. S. (2012). An examination of materialism, conspicuous consumption and gender differences. International Journal of Consumer Studies, 37(2), 189–198. doi:10.1111/j.1470-6431.2012.01099.x https://doi.org/10.1111/j.1470-6431.2012.01099.x
Lin, Y.-H., & Chen, C.-Y. (2012). Adolescents’ Impulse Buying: Susceptibility to Interpersonal Influence and Fear of Negative Evaluation. Social Behavior and Personality: An International Journal, 40(3), 353–358. doi:10.2224/sbp.2012.40.3.353 https://www.ingentaconnect.com/content/sbp/sbp/2012/00000040/00000003/art00001;jsessionid=49dldks9g37e.x-ic-live-03
Keech, J., Papakroni, J., & Podoshen, J. S. (2019). Gender and differences in materialism, power, risk aversion, self-consciousness, and social comparison. Journal of International Consumer Marketing, 1–11. doi:10.1080/08961530.2019.1647125 https://www.tandfonline.com/doi/abs/10.1080/08961530.2019.1647125?journalCode=wicm20
Keech, J., Papakroni, J., & Podoshen, J. S. (2019). Gender and differences in materialism, power, risk aversion, self-consciousness, and social comparison. Journal of International Consumer Marketing, 1–11. doi:10.1080/08961530.2019.1647125 https://www.tandfonline.com/doi/abs/10.1080/08961530.2019.1647125?journalCode=wicm20
Pechmann, C., Levine, L., Loughlin, S., & Leslie, F. (2005). Impulsive and self-conscious: Adolescents’ vulnerability to advertising and promotion. Journal of Public Policy & Marketing, 24(2), 202-221. https://www.jstor.org/stable/30000660?seq=1
Puklek, M., & Vidmar, G. (2000). Social anxiety in Slovene adolescents: Psychometric properties of a new measure, age differences and relations with self-consciousness and perceived incompetence. European Review of Applied Psychology, 50(2), 249-258.
Ranta, K., Kaltiala-Heino, R., Koivisto, A.-M., Tuomisto, M. T., Pelkonen, M., & Marttunen, M. (2007). Age and gender differences in social anxiety symptoms during adolescence: The Social Phobia Inventory (SPIN) as a measure. Psychiatry Research, 153(3), 261–270. doi:10.1016/j.psychres.2006.12.006 https://www.sciencedirect.com/science/article/abs/pii/S0165178106003969
Chaplin, L. N., & John, D. R. (2007). Growing up in a material world: Age differences in materialism in children and adolescents. Journal of consumer research, 34(4), 480-493.http://assets.csom.umn.edu/assets/93681.pdf
Hyde, J. S. (1990). Meta-analysis and the psychology of gender differences. Signs: Journal of women in culture and society, 16(1), 55-73. https://www.jstor.org/stable/3174607?seq=1#page_scan_tab_contents
Costanzo, P. R., & Shaw, M. E. (1966). Conformity as a Function of Age Level. Child Development, 37(4), 967. doi:10.2307/1126618 https://www.jstor.org/stable/1126618?origin=crossref&seq=1
Costanzo, P. R., & Shaw, M. E. (1966). Conformity as a Function of Age Level. Child Development, 37(4), 967. doi:10.2307/1126618 https://www.jstor.org/stable/1126618?origin=crossref&seq=1
Berndt, T. J. (1979). Developmental changes in conformity to peers and parents. Developmental Psychology, 15(6), 608–616. doi:10.1037/0012-1649.15.6.608 https://psycnet.apa.org/doiLanding?doi=10.1037%2F0012-1649.15.6.608
Becker, J. B. (2016). Sex differences in addiction. Dialogues in clinical neuroscience, 18(4), 395.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5286725/
Hser, Y. L., Anglin, M. D., & McGlothlin, W. (1987). Sex differences in addict careers. 1. Initiation of use. The American journal of drug and alcohol abuse, 13(1-2), 33-57.https://www.tandfonline.com/doi/abs/10.3109/00952998709001499
Bobzean, S. A., DeNobrega, A. K., & Perrotti, L. I. (2014). Sex differences in the neurobiology of drug addiction. Experimental neurology, 259, 64-74. https://www.sciencedirect.com/science/article/abs/pii/S0014488614000351?via%3Dihub
Kennedy, A. P., Epstein, D. H., Phillips, K. A., & Preston, K. L. (2013). Sex differences in cocaine/heroin users: drug-use triggers and craving in daily life. Drug and alcohol dependence, 132(1-2), 29-37. https://www.sciencedirect.com/science/article/abs/pii/S0376871612005017
Breslau, N., & Anthony, J. C. (2007). Gender differences in the sensitivity to posttraumatic stress disorder: An epidemiological study of urban young adults. Journal of abnormal psychology, 116(3), 607. http://www.epi.msu.edu/janthony/documents%20up%20to%202010/K05/Breslau_Gender%20differences%20in%20the%20sensitivity%20ptsd.pdf
Stein, M. B., Walker, J. R., & Forde, D. R. (2000). Gender differences in susceptibility to posttraumatic stress disorder. Behaviour research and therapy, 38(6), 619-628. https://www.ncbi.nlm.nih.gov/pubmed/10846810
Ditlevsen, D. N., & Elklit, A. (2010). The combined effect of gender and age on post traumatic stress disorder: do men and women show differences in the lifespan distribution of the disorder?. Annals of general psychiatry, 9(1), 32. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2917414/
Perkins, C. A. (1997). Age patterns of victims of serious violent crime. US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.https://www.bjs.gov/content/pub/pdf/apvsvc.pdf
Lieber A.(2020). https://www.psycom.net/depression.central.major.html
RAMH (2020). https://ramh.org/guide/gender-differences-in-mental-health/
Baron-Cohen, S. (2009). The essential difference: Male and female brains and the truth about autism. Basic Books.
Auyeung, B., Allison, C., Wheelwright, S., & Baron-Cohen, S. (2012). Brief report: development of the adolescent empathy and systemizing quotients. Journal of autism and developmental disorders, 42(10), 2225-2235.https://link.springer.com/article/10.1007/s10803-012-1454-7
The Guardian. https://www.theguardian.com/life/table/0,,937441,00.html
Daros, A. R., Zakzanis, K. K., & Ruocco, A. C. (2013). Facial emotion recognition in borderline personality disorder. Psychological Medicine, 43(9), 1953-1963. https://www.researchgate.net/figure/Demographic-and-clinical-characteristics-of-borderline-personality-disorder-patients-in_tbl1_265008346
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