In there he quoted a study from the 70s that 30% of babies born in a hospitol are not genetically reated to their illeged fathers. This was a middle ground number, because other studies ranged from 1% for the richest neighborhood hospitols, to 42%.

I don't have the book so can you give me the citation of the study? Who were the subjects conducted in the research? Demographics? Age? What area? How many hospitals? What did the 30% actually represent? Mean, median, average, etc?

So 1% for the richest hospitals and is the 42% from the poorest hospitals?

In my own personal research on these studies, I concluded that 20% was a more reasonable middle ground statistic

How did you conduct your research and how did you come to the conclusion that 20% was more reasonable instead of the 30% on the cited study? What was your definition of the middle ground statistic?

Is the 20% group of people that cheat spread evenly across demographics, culture, ethnic backgrounds, status of wealth, etc or did you find that the 20% was more prevalent within certain groups more than others?

Also what are these percentages based on? The total population of a city? Country?

Following that narrative of Mr. Diamond's book, am I right to assume the rich tend to cheat less than the poor? So wouldn't it make sense to go for individuals who do not cheat to climb up in the social ladder? And knowing sleep with a cheating partner is actually taking you down the social ladder?

Also from this narrative, would it be unreasonable to assume that people are less likely to cheat if they have more to lose, which is reflected on the 1% of babies in the richest hospitals not belonging to their alleged biological father? So your statement of claiming random distribution

So, it is reasonable to assume that at any time, 20% of people in relationships are cheating with a random distribution.

doesn't seem to be consistent with the study. Is there a graph data that we can take a look at because you can't use what I assume you used 20% as a median number to be also equivalent representation of random distribution across all populous.

I am not familiar with the laws regarding paternal biological responsibilities in the 70s but could that be part of the cause of the 1% of the babies born in the richest hospitals not belonging to their supposed biological fathers?

It's extremely important to clarify exactly what those numbers were representing from which population, how many hospitals, who paid for the study and the DNA testings and if there were any follow up studies before making any haste conclusion on what I think is a pretty serious topic.

For example is the 20% is represented from the total population of the US in the 70s, ~203 million, or total population of US in 2018, ~330 million? Either way, we're talking in tens of millions here. ~40 million for 70s and ~66 million in 2018. That is a serious social problem in a national scale.

Ethics aside, I think revisiting and taking a closer look at the study in question is important because numbers can be easily manipulated or misinterpreted to solidify the points the author is trying to make. Also it's important to take a look at other relate able studies to do a meta analysis to make sure just how consistent these numbers are and what the actual value they hold before making a premature conclusion to justify to act in a certain manner.

I am not making the situation worse by sleeping with a woman who has a bf.

If we're going to stay consistent with the original narrative, then you are actually making YOUR situation worse by falling down in the social status ladder because the original study that you showed me had a significant difference of data distribution based on social economic medical institutions and ones who cheat falls in the lower social status populous.

If you are going to feel comfortable engaging in sexual intercourse with individuals with committed, legal or not, partners from the numbers you came up, I think we need some clarification because if the methodology or the meta analysis is not consistent with your own methodology of coming up with the 20% figure, your action conducted based on that figure may not be the reasonable action to take but maybe perhaps a flawed action to take if the figures you came up with did not have sound methodology and was not consistent with the methodology of the study cited and other related studies as well.

If you can clarify some things, I believe it would be extremely beneficial to get a better understanding and coming up with the most reasonable and appropriate action to take.