Can samples be considered as individuals Let's say to estimate the mean age of teenagers in a certain country using sampling, I take 10 000 samples of 100 people in that country. Would it be correct to say that the samples are the individuals, the variable measured (on the individuals) is the mean age of the 100 people in a sample? The population therefore would be all the possible samples of size 100. I'm asking because in a sampling distribution that estimates the mean of a population, the frequency of individuals are in fact the frequency of the samples.

It’s important to keep track of what’s going on in a sampling distribution.
If we have some random variable $X$ and want to know its distribution, we calculate the CDF, and that is the distribution. This is the distribution of every individual in the population under consideration by $X$.
In a sampling distribution for some statistic that is derived from $X$, such as the sample mean $\bar X$, we want to know about samples drawn from $X$ that have the statistic calculated. Thus, we draw $n$ individuals from $X$, calculate the statistic, and call that quantity an individual value of the sampling distribution. To get the whole distribution, keep on doing this.
In reality, we typically have only one observation of a sampling distribution, though bootstrap methods aim to synthesize an approximate sampling distribution by sampling from the empirical distribution, with the idea being that, if we cannot go back to the original distribution and sample from it, the next-best idea is to sample from a representative sample.
