To the second link
"Bubble sort always performs n-1 passes through the data (where n is the amount of elements), and it always performs (n-1)+(n-2)+...+1 comparisons regardless of how the data is organized to begin with."
That is just false. 1 pass and n-1 comparisons then stops for already sorted data is what you get. An implementation that doesn't show that characteristic has been either deliberately or accidentally pessimized to behave poorly. You can gimp any algo to make it look bad. Quicksort without randomization on a pathological case is O(n^2) for example and nobody cares for the overwhelming majority of practical purposes. If your definition of bubble sort is that it must be O(n^2) always then we're not using "bubble sort" to mean the same thing and it's pointless to continue the discussion.
Bubble sort is usually operates on data in place. I don't know how to do an efficent in-place selection sort for mostly sorted data, maybe it's possible? You pay for additional copies in both space and cpu cycles. 2xn space for selection usually - but maybe this can be avoided without paying a very high time overhead, (eg find the spot, ripple all data below the spot down to the hole where you selected to open a slot for insert or similar).
Count the memory operations, ie number of memory reads and number of memory writes for a given set of data comparing the two algorithms.
Suggestions: Write 50 odd lines of C code to see the actual effect in cpu cycles. Craft data to make each algorithm dominate the other, it's really interesting to see.
I'm disinclined to say "Never uses algo X, always use algo Y!" Because it's really hard for that to be sensible given all the various shapes and sizes input data takes. Know your data is always really, really good advice.