Here's an algorithm (in Python) that is exactly equivalent to the one in the paper:

    def pseudobubble(lst):
        n = len(lst)                  # give a name to the list length
        for i in range(n-1, 0, -1):   # i will range from n-1 down to 1 inclusive
            if lst[i] > lst[i-1]:
                swap(lst, i, i-1)     # high values bubble down
        for i in range(1, n):         # 1 to n-1 inclusive
            for j in range(i, 0, -1): # i down to 1 inclusive
                if lst[j] < lst[j-1]:
                    swap(lst, j, j-1) # low values bubble down

The first pass of this algorithm (bubbling high values down, one time only) may do different things than the first pass of the paper's algorithm, but that's not relevant.

All comparisons and swaps in the code you quoted are made between adjacent elements. It's local in a way that behaves very nicely for an external sort on a tape drive.

The code in the paper compares and swaps non-adjacent elements nearly every time. It is absolutely horrible for an external sort on a tape drive. It's just not a bubble sort, nor is it sort of like one in any key behavioral detail.