It's a 2 hour video essay that covers psychometry generally as a lens to understanding a book called the Bell Curve that was a flashpoint for questions about the validity of IQ science generally (but most especially how it applies to race). It took a good chunk of my Sunday to get through it, but it was really enjoyable and gave me a ton of insight into a ton of buzzwords and studies I had heard of but couldn't really dig my teeth into.

I think with this topic, getting a briefer, less nuanced summary than something like this would be a mistake because of how much misunderstanding of these topics permeates popular culture. The video also provides a number of studies and books to keep going beyond the relatively breif 2 hours of content it provides.

It uses the famed/infamous book the Bell Curve as a case study and delves into how they were originally created, how they are updated, how the term hereditery when used in genetics means something that is sometimes counter-intuitive to the definition used in popular culture (for example whether someone wears earings has high heritability, whereas having 2 arms has effectively zero herritability) the statistical meaninfullness of factorization (G-factor) of domains of IQ into a single numerical value, how these domains came to be defined, the current state of understanding regarding the local vs enviornmental source of IQ for individuals, how the Flynn effect was observed, etc.

But to answer a bit of your earlier question. When IQ tests are created, they create a set of questions, test it on a sample group, and set the average value to 100 and higher/lower scores depending on what the distribution of correct answers is. The Flynn effect happened because researchers noticed while the average for new tests always is set at 100, people scoring 100 on a more recent test were generally scoring even higher on previous years tests. The article of the reverse Flynn effect is a little bit sensationalist because as it mentions while some areas (like Spatial Reasoning) are improving, others are apparently starting to get lower. This calls into question a bit the idea of a G-Factor which is an assumption that their is a common factor of intelligence that covaries across all IQ domains (spatial reasoning, reaction time, etc... ) which is the theoretical reasoning behind IQ being meaningfully represented as a single numerical value rather than a multi-dimensional value.