$\star$ Suppose that an algorithm uses only comparisons to find the $i$th smallest element in a set of $n$ elements. Show that it can also find the $i - 1$ smaller elements and the $n - i$ larger elements without performing any additional comparisons.
A strict proof might require a more advanced proof apparatus than I command (like graphs and adversary algorithms, for example?), so I will just sketch it briefly.
In order to determine the $i$th order statistic, any algorithm needs to establish in some way that there are $i - 1$ elements smaller than the result and $n - i$ elements larger than the result. We can visualize the algorithm as a directed graph, where all the elements are edges. Each comparison introduces a node from the smaller to the larger element. To produce a result, there must be $i - 1$ elements that (transitively) point to the $i$th order statistic and $n - i$ elements that the $i$th order statistic (transitively) points to. There cannot be more (property of the order statistics) and if there are less, then there are elements whose position in regard to the $i$th order statistic is undetermined.
In order to find the result, the algorithm needs to build the knowledge presented in such a graph and it can use it to return the sets of smaller and larger elements.
As an example, both algorithms presented in the chapter leave the array partitioned around the $i$th order statistic.