The real question is “shirts without stripes” really a query people enter? Or representative of a real pattern in the data?
Citation needed.
As far as my personal observations go, Google is NOT optimized for long tail at all. It is always trying to return most popular results from cache of most popular results. Once the cache is exhausted, Google starts to return completely irrelevant trash (anything after first two pages of search is pure spam and meaningless keyword soup).
If you try to look up some obscure keyword and find nothing, try again after couple of months. There is a very high likehood, that you will see dozens of "new" results — most of them being from several years old pages. Perhaps, the actual long-tail searches still happen somewhere in background, but you are not going to see their output right away — instead you need to wait until they get committed to the nearby cache.
Another alarming change, that happened relatively recently (4-5 years ago), is tendency to increase number of results at expense of match precision. A long time ago Google actually returned exact results when you quoted search phrase. Then they started to ignore quotes. Then they started to ignore some of search terms, if doing so results in greater number of results. Finally, Google gained horrifying ability to ignore MOST of search terms. OP's example probably has the same cause — Google's NLP knows the meaning of word "without". But Alphabet Inc. can't afford to hose all those websites, that use AdWords to sell you STRIPED SHIRTS. This would mean a loss of money! THE LOSS OF MONEY!!!
And since most search applications are basically just finding you the results with the most keyword matches, with a little bit of extra magic thrown in, the above is basically what you see.
These queries are basically the equivalent of optical illusions in cognitive psychology when studying the visual system -- seeing how the systems break tells you a lot about how they work.
Have you ever seen shirt dresses in your dress shirt queries, or vice versa? The search application isn't caring enough about bigrams and compound words.
Have you ever seen bowls in your bowling queries or fish in your fishing queries? The search application is over-stemming.
Natural language search is a real pain on any general purpose search application, particularly ones that have to deal with titles. The obvious simple fix to this query is to rewrite [x without y] to [x -y], but then when someone goes to search for [a day without rain] or [a year without summer], you are going to totally break those queries.