
DarkStar
Luminary
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It has generally been noted that males exhibit greater variability in physiognomy -though this could in part rest in the fact foids are much more hiveminded- though even Darwin & others observed this across various species.
Of course, if something extends to physiology we can make a safe assumption that it can also impact mental cognitive abilities:
View: https://x.com/powerfultakes/status/1925074699564024303
So let's see if this general hypothesis holds up.
To start with, a General Cognitive Abilities test(CogAT) conducted on a large body of students overtime found that males overall seem to have more variability within the reams of non-verbal reasoning, or that of solving problems more related to that of shapes. In other words, it's how an IQ test should be done:
www.sciencedirect.com
Furthermore, similar results appear when analyzing Quantitative reasoning:
www.sciencedirect.com
When it comes to the factors of time-preferences, risk-taking, and also social choices- converging evidence helps to supplant this theory:
Aside from at age two, males exhibit a much greater range of variability which is twice that of foids by age ten.
www.sciencedirect.com
Another comprehensive study, tracking the progress over thirty years or so, found that results have remained mostly consistent despite the gap somewhat closing:
Once again, it is great to see the fundamental aspects of the blackpill -that of basic human biology- proven with science.
This guy also explains it very well, and i'd recommend checking it out:
inquisitivebird.xyz
Possibly interested users:
Of course, if something extends to physiology we can make a safe assumption that it can also impact mental cognitive abilities:
View: https://x.com/powerfultakes/status/1925074699564024303
So let's see if this general hypothesis holds up.
To start with, a General Cognitive Abilities test(CogAT) conducted on a large body of students overtime found that males overall seem to have more variability within the reams of non-verbal reasoning, or that of solving problems more related to that of shapes. In other words, it's how an IQ test should be done:
For nonverbal reasoning, mean differences were nearly non-existent. However, greater male variability was again observed, with males showing 15–23% greater variance than females. This resulted in consistent male–female ratios (with 1.2 to 1.3 males for every female)

Sex differences in reasoning abilities: Surprising evidence that male–female ratios in the tails of the quantitative reasoning distribution have increased
Sex differences in cognitive abilities, particularly at the extremes of ability distributions, have important implications for the participation of me…
Furthermore, similar results appear when analyzing Quantitative reasoning:
CogAT 7 showed mean differences favoring males that were markedly larger than the previous forms (though still below the cutoff for “small” effect sizes; Cohen, 1988), with CogAT 4 having the second largest mean differences.
It also found that virtually no noticeable difference -which seems to consistently fall around one SD- shows to us that foids are roughly similar to us in terms of verbal reasoning, yet are mogged by males in many other metrics:For example, on CogAT 7, the male–female ratio for the top 5% of quantitative scores was 2.02 while at the top 1% it was 2.77. Wai et al. (2010) found even more striking differences, especially in earlier years (surging up to 13.5:1 with the most stringent cutoffs in the early 1980s).7 Hedges and Nowell (1995) found in the 1960s Project Talent data (the only dataset in their study with sufficient score ceilings to support such estimates) that male–female ratios were 1.3 in the top 10%, 1.5 in the top 5%, and 7.0 in the top 1%.
The data revealed small changes in verbal and nonverbal reasoning and more pronounced changes in quantitative reasoning which warrant further investigation and replication in other datasets.

Sex differences in reasoning abilities: Surprising evidence that male–female ratios in the tails of the quantitative reasoning distribution have increased
Sex differences in cognitive abilities, particularly at the extremes of ability distributions, have important implications for the participation of me…
When it comes to the factors of time-preferences, risk-taking, and also social choices- converging evidence helps to supplant this theory:
The estimated risk ratio is 1.25, indicating that for every 100 women there are 125 men opting for either the most patient or most impatient option. The fourth indicator is the standard effect size measure in the variability literature, the ratio between male and female variance in the dependent variable. With an estimated variance ratio of 1.15, it ranks in the intermediate range of effect sizes found in other research on GMV such as cooperation, mathematical performance, and verbal skills as well as spatial performance (10).
This study also analyzing the hypothesis amongst children found this deviation in g-scoring:For every 100 females, there are 150 males exhibiting full impatience. The three intermediate categories are more frequently chosen by female subjects, while the most patient option is again highly significantly more popular among male subjects, with 125 male subjects for every 100 female subjects.

Aside from at age two, males exhibit a much greater range of variability which is twice that of foids by age ten.

Sex differences in variance of intelligence across childhood
Why are males over-represented at the upper extremes of intelligence? One possibility for which there is some empirical support is that variance is gr…
Another comprehensive study, tracking the progress over thirty years or so, found that results have remained mostly consistent despite the gap somewhat closing:
However, it does imply that a good percentage of this mainly is due to verbal reasoning, with males still having more SD overall in quantitative reasoning:One factor in the debate surrounding the underrepresentation of women in science technology,
engineering and mathematics (STEM) involves male–female mathematical ability differences
in the extreme right tail (top 1% in ability). The present study provides male–female ability
ratios from over 1.6 million 7th grade students in the right tail (top 5% in ability) across
30 years (1981–2010) using multiple measures of math, verbal, and writing ability and science
reasoning from the SAT and ACT. Male–female ratios in mathematical reasoning are
substantially lower than 30 years ago, but have been stable over the last 20 years and still
favor males. Over the last two decades males showed a stable or slightly increasing advantage
in science reasoning. However, more females scored in the extreme right tail of verbal
reasoning and writing ability tests
displays the male–female ratio in 5-year seg-ments for students scoring at or above each respective level on the SAT-M. We used 5-year segments because some individual years had cells with no females and because it also helped decrease the noise related to individual year ratio fluctuations to uncover the stable trend. From 1981–1985, the male–female ratios at the ≥500, ≥600 and ≥700 levels were 2.61 to 1, 5.82 to 1, and 13.5 to 1, respectively, thus replicating previous findings (Benbow & Stanley, 1980, 1983; 2.1 to 1, 4.1 to 1, and 13 to 1 respectively). From 1986 to the present, the male–female ratio declined at several levels and time periods. As can be seen in Fig. 1,the ratio of students scoring ≥700 (top 0.01%) on the SAT-M began to fall immediately after 1981–1985, but has remained relatively stable for the last two decades at roughly 4 to 1,with the most recent time period (2006–2010) indicating a ratio of 3.83 to 1. Thus, we confirm a decline, although not to the level given by Stanley and commonly cited in the research literature. Among perfect scorers (800) on the SAT-M, the ratio was 6.58 to 1 for 2006–2010, showing that even at the utmost right tail, the male–female ratio is now well below 13 to 1![]()
Once again, it is great to see the fundamental aspects of the blackpill -that of basic human biology- proven with science.
This guy also explains it very well, and i'd recommend checking it out:

Understanding Greater Male Variability
The Greater Male Variability Hypothesis (GMVH) suggests that males exhibit greater variance than females in their cognitive abilities.

Possibly interested users:
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