The Human Codex
Politics is exhausting. Say the wrong things to the wrong people, and you're suddenly on a witch hunt -- as the witch. You're also expected to know everything about everything. So, I've distilled some key ideas below which can take you pretty far in navigating discussions around psychology, society, and politics.
Empathy Divide
Figure 1: Heatmap of Empathy
There is a big observable difference between people who identify as conservatives and liberals on how much they care about people and things around them. The above figure does a great job at explaining the difference between the two.
The key takeaway is how comparatively, conservatives do not assign as much moral value to people outside their acquaintances (ring 5) while most liberals assign at least some (if you have time, read the full study, it's very interesting). I also believe this indirectly shows how each of us has a finite amount of total empathy, and that in general the more we direct our empathy to abstract further-away entities, the less we have for real entities close to us, and vice versa.
Individuals Seek Belonging
Humans inherently strive to be a member of a group. Evolutionarily speaking, you could not survive without being part of a group. Humans hunted in groups, babies were raised in groups, and so on. While modern luxuries have made group membership not strictly necessary, we are still biologically hardwired as social creatures.
This desire to belong is why we are so eager to latch onto a group identity. Whether this is with our family, friend groups, nationalities, ethnicities, religions,or political parties, we are hardwired to find a group, a label, to belong to. I believe any group can be categorized into one of two types: birthright or ideological. Birthright groups are those that are given to you by birth, such as your family, nationality, and ethnicity. Ideological groups are those based more on beliefs, such as political parties, religions, and so on.
With the rise of globalism and Internet use, birthright identities have become less meaningful. For example, in mixed race families, it is hard to wholly latch onto a nationality or ethnicity. Moreover, it's not guaranteed that you will internally identify with your nationality or ethnicity. For example, someone born outside of America could potentially feel a stronger sense of belonging to American culture than to their own ethnic motherland(s).
Unlike groups given by birthright, ideological groups are more fluid -- hence easier to "join", but also reflective of your own tastes. I believe this freedom of choice is why today, many people care more about "what you believe" rather than "what you are". It's a more deeper reflection of who you are as an individual.
A lot of our beliefs are also a result of mimicry. We mimic the beliefs of the group we are a part of. This is a defense mechanism against the out-group.
The Normal Distribution
Also known as the Gaussian or the bell curve, this probability distribution is the most common one observed in nature (the reason behind this is because of the central limit theorem, but that is not within the focus of this blog).
Figure 2: Normal Distribution
What you should take away from this is that when discussing or understanding anything, you must remain cognizant that most conversations revolve around the distribution, not the individual data points. I see so many examples of people focused on outliers rather than the distribution. For example:
Claim (on distribution): "Pitbulls are dangerous"
Rebuttal (individual data points): "But my pitbull is friendly!"
This rebuttal doesn't refute the shape of the distribution in any way. It only shows that there are exceptions to the rule.
Also, observe how small the tail ends of the distribution are. It requires 2 standard deviations away from the mean to be considered an outlier in the top/bottom 3%. This means that most people are not outliers. Let me say that again. Most people are not outliers. Not everybody can become a top tier athlete, renowned musician, grandmaster chess player, or movie star.
Here's where it gets interesting. Mathematically speaking, the tails of the distribution are incredibly sensitive to changes in the mean and standard deviation. Feel free to explore the math on your own, but I want to illustrate its implications in the next section.
Understanding the normal distribution is key to understanding the world.
Small Differences Matter
I want to take a moment to highlight just how impactful small shifts in the normal distribution are. Small, really small differences in the mean and standard deviation can have a huge effect on the number of outliers. I want to highlight this with a gender difference example.
Humanity is composed of only men and women (ignore outliers, and just take it as an assumption for the sake of argument). We are a species of two sexes. There are huge differences between men and women (remember that we are always referring to the distribution!).
The obvious ones are related to physical attributes. Men are on average taller, have more muscle mass, have denser bones, store more fat in their abdomen than thighs, have deeper voices, have higher capacity and tendency for violence, etc. etc. etc.
Note: there is an idea called the male variability hypothesis, which suggests that men are more variable in their traits than women. This affects the shape of the bell curve.
Figure 3: IQ Variance Between Men and Women
This is why you see more variance in attributes like height, IQ, and so on. I.e. there are more dumb men than dumb women, and more tall men than tall women. We can explore this in more detail by examining a study by Lynn (2011).
The Kicker
Though the difference between the study's recorded standard deviations (15.235 vs 14.085 for M and F respectively) is small, such differences can have a huge effect on the number of outliers. For example, in the model where IQ follows a normal distribution for each gender with the means and standard deviations as outlined in this study, one would expect nearly twice as many boys than girls with an IQ above 130. To be precise, approximately 3.05% of boys and approximately 1.57% of girls would have an IQ of 130 or higher in this model.
These differences would grow wider as one gets farther from the mean. For example, using the same model as the previous paragraph, one would expect more than six times as many boys as girls with an IQ of 160 or higher.
Recall that we are only examining IQ here. Such small discrepencies in mean and standard deviation exist in many other attributes. Moreover, they also exist for other groupings beyond gender. Here, we only applied it to gender. Other groupings like nationality, ethnicity, religious affinity, and so on also have differences in mean and standard deviation of many attributes.
Understanding how small differences in the mean and standard deviation affect the number of outliers is a key to understanding why we *might* see certain disparities in society.
Self Perception
If you're ugly, obese, and/or ungroomed, every day when you look in the mirror, you see a reminder of your inadequacy. This negative self image can easily breed resentment and anger within you. It's bound to affect your thoughts. Your self-perception is behind every action you take, every word you say, and every decision you make.
When someone has an opinion on something, their self-perception is reflected in their opinion. The aesthetic divide between the ugly and beautiful is reflected in many things in the world. Keep this in mind when engaging with others.
The most judgemental are usually the most insecure. Success reminds ugly people of their inadequacy.
Hope this helps you understand the world a bit better.