To Norlite, Part 1.
I haven't really read much from the people who oppose this system. But I think that the argument against discarding so much data (dropping 4 judges from the sitting panel of 14, then dropping 4 more for high and low marks) goes something like this.
There is, in the grand cosmic scheme of things, a Right Score for each performance. This is the score that God would give, were She a figure skating judge instead of just an enthusiastic fan. (I wonder if God would be ticked off if the computer randomly threw out Her marks.)
Anyway, since we don't know what this Right Score is, it can be best approximated in principle by, let us say, taking the average of all the marks that might ever be given for that performance by all the properly qualified figure skating judges that are, ever were, or ever could be. In the language of sampling theory, this is the "population." The Right Score is the mean score of this population.
To attempt to get the best possible estimate of the Right Score, we take a "sample" from this population -- the panel of judges. The average mark of the panel of judges is the best unbiased estimate that is available to us of the Right Score (i.e., the population mean).
The "standard error" for this elementary problem in statistical estimation is S.E. = Sigma/(square root of n), where sigma is the standard deviation of the population (we can estimate this by the standard deviation of the sample), and where n is the sample size. That is, as you include more and more judges, the sampling error goes down by a factor inversely proportional to the square root of the number of judges. If you quadruple the size of the judging panel, you cut the error in half.
Conversely, if you cut a panel of 14 down to a panel of 5 (pretending for a moment that this is done randomly, without the "high and low" thing), this increases the sampling error by 67% (sqrt 14 / sqrt 5 = 1.67).
So, bottom line: You should have as large a judging panel as possible and use all the data available in making your estimate of the Right Score.
MM