This one sentence sums up the source of trouble in Stanley Fish's widely-panned blog post:
My [Fish's] criticism was a proto version of theirs [Archibald and Feldman whose book Fish was pitching], absent the massive data and the economic sophistication.
Here, he admits two reasons for trusting Archibald and Feldman: their position agrees with his own point of view; and economists wielding data.
Under reason one, it wouldn't matter if the analysis makes sense or not; his support is based on their agreeable conclusion. It is shocking that he so blatantly and openly says this. Making the numbers fit the story, rather than making the story fit the numbers, is a cardinal sin.
Reason two reveals his laziness; if he had called up any economist or statistician, chances are he or she will have major problems with Archibald and Feldman's analysis. The quantity of data has nothing to do with the quality of the analysis. That's the first thing your statistics teacher should be telling students. Higher "sophistication" (or "complexity") of analysis also does not guarantee better quality -- but it does guarantee slower understanding. That is not the first lesson but still an important lesson in statistics.