You can read the second part here.

The subject of PUAs and seduction gurus seems to be a matter of special interest among my followers. In a recent survey I conducted in Patreon this is the winning topic, so I will try to analyze it as best I can.

Anyway, if feminism already falls outside my academic field of expertise, seduction does it even more, so what I say may not be as original or as interesting.

On the other hand, I will divide the analysis into two parts, because I think I should start by establishing a general basis of how attraction between men and women works, before moving on to the different approaches people take.

This first video is dedicated to expectations in a relationship, and whether it is really true that girls have to deal with unfair expectations. The second part will be dedicated to the theories of the PUAs and the gurus of seduction as such.

We have already seen in previous videos how men tend to be less selective than women in general, and how this has to do with the biological factors of reproduction.

Probably the study with the largest sample that shows this most clearly, is the famous OkCupid data analysis, which everyone who has touched on this topic has already commented on, and yet I think more information can still be extracted from this same source.

Essentially these data tell us that men value women in a balanced way, with a majority of them scoring around 5 out of 10, and an equal number of cases on each side of the distribution, while women would tend to dismiss a majority of men in attractiveness, with 80% of them below 5.

Considering the enormous theoretical value of these graphs, it is not surprising that their use among PUAs is frequent, but It has also given ground to two particularly prevalent myths in this regard.

The first is that this is an internally inconsistent assessment by women.

I have seen malicious comments pointing out that it is impossible for a majority of men to be below average, and that women probably don't know about mathematics.

But this is mathematically possible, and those who say this are probably confusing the mean and median, which has a lot to do with the other frequent mistake.

The second myth is that women's assessment of men is shaped like a distorted gauss bell. This conclusion is understandable if we start from the fact that the graph of female attractiveness does seem to be a normal distribution, so for those who support the idea that feminism has created unrealistic expectations among young girls, the idea that their assessments show a distorted view of reality makes sense.

However, for those who support the opposite idea, that feminism is a manifestation of biological biases that have been latent for millennia, things are different.

My hypothesis is that this is not a normal distribution, but a *log-normal* distribution. This may seem like a terminological detail of no importance, but here is the key.

A normal distribution is the result of averaging between multiple independent variables. A *log normal* distribution is the result of multiplying those variables with each other.

If this is true then the key to women rejecting as many men on pages like OkCupid would be that their traits would not be perceived independently but would all affect everything else.

In other words for a man, a girl with a body of 10 and a face of 0 would be the average of both scores, a 5. For a woman a man with a body of 10 and a face of 0 would be a 10 times 0, a 0.

Since genetically each of a person's traits is independent in practice, this ensures that most women will fall around a 5, since on an arithmetic mean of independent values, abnormally low scores tend to be offset by abnormally high ones, while most men will have very low scores, since a critical flaw in just one of their characteristics is enough to sink their overall attractiveness completely.

On the other hand, this would also allow us to estimate how many factors are relevant in the field of seduction, and thus compare them with the different models used by PUAs and seduction gurus, later on, and see how successful they are.

One of the properties of multiplicative distributions is that the greater the number of factors, the higher the score on each of them must be to obtain a good overall result.

Based on this and from the famous 80/20 statistic, i.e. that 80% of girls are interested in the same 20% of boys, we can deduce that the requirements of women are really not many.

According to my calculations we would be talking about 3 to 4 factors. The question would be to determine which ones.

But before we go on to discuss the proposals of the PUAs and so on, it seems to me that I should also talk about the model of the attraction differential, and I believe that this has two particularly important repercussions.

The first is that it explains the apparently paradoxical phenomenon of couples in which the man is much less attractive than the woman without resorting to malicious hypotheses, such as that he must have a lot of money or the like, and also without completely denying the observable tendency of women to be more selective than men.

And the second is that it also accounts for the more common social courting dynamics. So what this model consists of is taking the functions of the distribution of the attractiveness of each sex and calculating its integral in order to compare the subjective attractiveness of each individual according to his or her percentile.

Basically this means that we can take the data from this OkCupid graph and convert it into this other graph that we have just seen, which represents how each person is perceived according to their place on the scale.

**Incise**:

For those who have somewhat forgotten the subject of derivatives and integrals, essentially what has been done is to take the function that describes how the variable of attractiveness changes with respect to the X axis, and obtain the total accumulated attractiveness of each of those individuals.

In more intuitive terms, we could say that this is like obtaining position from speed. That is, position is the integral of velocity with respect to time, and velocity is the first derivative of position: If you know what velocity an object has at each point in time, you can calculate its position. The same applies here with respect to perceived attractiveness and position in the hierarchy.

According to this last graph, a couple in which both members are in the same percentile, is socially perceived in a way that she is subjectively more attractive than him in all cases, and that difference is greater the closer to the median that value is.

In practical terms this model predicts several interesting things that we could explore in a future video, such as that the most stable couples are those formed by people at the ends of the spectrum.

But for the moment it is sufficient to point out that the ideal couple according to men would be the one who is at the same point of the curve as he is with respect to the horizontal, while the ideal couple for her would be the one who is at the same point with respect to the vertical axis.

I believe this model explains quite well the basis of the intra and intersex competition that we had seen in other videos, because the interests of each sex do not align perfectly, and therefore it is necessary for all couples to agree on and reach mutual commitments.

I also believe that it is a quite useful theoretical model, because it provides an objective and quantitative basis with which to contrast its rival hypotheses. In other words, here the criterion of what each individual is looking for is very clear, a person of the opposite sex that corresponds to his or her own attractiveness, or superior in the proportion that determines the attraction differential. There is no room for interpretation.

On the other hand the model is not perfect, like any scientific model. In that sense all theories are ideal approximations to reality. The question is not whether they are exact, but whether they are useful, and as a theoretical fiction I think this is the case for several reasons.

In the first place, although the data are extracted from the online behavior of people, scientific studies have found that this sample represents well the general population with respect to their sociability, self-esteem and sexuality.

In many other laboratory studies it has also been confirmed that men are more consistent in their assessments of female attractiveness than women, and in general women are more selective in roughly the same proportions as our initial statistics indicated.

Finally and more important, the same Pareto distribution can be found in African aboriginal tribes, indicating that this dynamic is not cultural, but part of natural human behavior, and also in groups of chimpanzees, which is a clue to their evolutionary origin prior to our own species.

All of this, together with what we have already discussed in previous videos, I think is quite strong evidence that my model can be generalized to the common population.

In any case, it is necessary to respond to a criticism that is usually seen in this type of findings by sectors related to feminism, and that is that although women have higher standards than men, in terms of their valuation, this would not be fulfilled if we observed their behavior in practice.

As a hypothesis it might make sense if we consider that in scientific studies both sexes are equally bad at describing what attracts them to a couple when we test it with their real choices.

However, in this case it's different, since it's not an exercise of introspection, but of describing whether or not one is attracted in real time. The argument that is usually given comes from the same original source as OKCupid, and is that even if women give low scores to these men, they still send them messages, so it would be the men who would have unrealistic standards.

The only problem with this argument is that it is wrong. The blog itself indicates that these graphs are not standardized. In other words, the graphs that show the number of messages sent by each sex only show the percentage of total messages received by each level of attractiveness, but do not take into account the number of people in each of those levels.

Obviously, on a page where most users belong to the ugly group, most messages will be received by the ugly.

The error is understandable considering that even the same owner of the page, with all the data in front of him, still continues to interpret the results according to the narrative that men have unreasonable expectations about women, and the proof he gives is the graph that shows how the growth curve of the number of messages received according to the attractiveness is steeper for girls. That is, the most attractive girls receive many more messages than the least attractive ones, while the difference is not so great among men.

However, if we look at the graph, we can see that it is not given in total numbers, but in multipliers.

In other words, it gives us the proportion of women among themselves and of men in proportion to other men, but we cannot compare men and women to each other, because both curves are on a different scale.

In fact, the women's curve is stretched vertically, but that cannot be known from that graph alone, because no absolute numbers are given.

On the other hand, we can extrapolate those absolute numbers from the graph that appears on page 124 of Dataclism, which does contain numbers of total messages and uses the same database.

If we do the math again, taking this into account, there are no significant differences in the proportion of attention of the opposite sex received by the most attractive individuals of each sex compared to the least attractive.

In conclusion, by adjusting the data according to the proportions of users of each sex according to their level of attractiveness and the number of messages sent and received, the behavior of men and women is identical with respect to members of the opposite sex who are considered subjectively equal.

Therefore, we cannot say that the contact habits of women change in any way their assessment of men. The model of the attractiveness differential is maintained.

Moreover, this conclusion has some support in the scientific literature. In both men and women, the expectations are the same.

Ideally, you want a partner who is about 25 percent more attractive than you are, but because the level of attractiveness is subjective and determined differently between boys and girls, that makes desirable men proportionally fewer.

In any case, it is not true that there are patriarchal values that make men have unhealthy expectations of women.

Obviously men have preferences, but these are quite reasonable on average, and I think that's all that needs to be said on the subject of expectations for now.

In the next part of the video we will analyze the theories of the seduction gurus and see if any of them really works.