Does A Distinctiveness Score Prove Anything About A Generated Page
Does a distinctiveness score prove anything about a generated page
The question arrives every time a spam update lands, and it comes in the same shape: someone has a pool of generated pages, a checker that reports them as very different from one another, and a suspicion that the figure is not answering the question they actually have. They are correct to be suspicious, and the reason is easier to demonstrate than to argue about, because both parts of it can be tested on the same set of pages in about a second.
I produce location pages for one service, one page per city, from a skeleton with a lot of synonym slots. My checker says the pages barely overlap, which everyone tells me is what you want. But the search engine's own policy lists synonymising as an example of the thing it moves against, so which one am I supposed to believe, my score or their page?
Both, since they are not measuring the same thing. The policy language is about what a batch of pages is for and how little it adds for the person reading it; the method is explicitly not the violation, and the same sentence says so whether a human or a system did the writing. A similarity score, however, measures variation density over short runs of words. A pool can push that score as far as it goes and still express one thing in many costumes, which is the phenomenon the policy example depicts rather than the opposite of it. The first thing to determine is not how different the pages look but where their differences came from.
There is a test that shows where the differences came from, and it requires one pass. Replace every value that arrived from data, the town name included, with a placeholder, and check the pool again. If what remains is many pages that are still distinct, the template produced them and the reader receives one page every time. If what remains collapses to a single page repeated, the data was holding the difference, and the pages are worth as much as that data behind them. That second part the test cannot settle for you, and no measurement will.
Why the score shifts the wrong way when the documents carry data
Construct the same pool twice. Once with synonyms and nothing else varying, and once with no synonyms at all but a number of real values bound per page, the sort of thing a listing would contain. The synonymised pool scores as barely overlapping. The pool bearing values scores worse, because facts repeat across pages in the same sentence patterns and short word runs survive. By the score, the pages built to say something particular look like the suspicious ones, and the pages stating every town the same thing in different adjectives look clean. That reversal is the whole answer to the original question: the score cannot tell a pool that says something from one that merely looks varied, so a good number is not evidence of anything the policy weighs and a poor one is not an charge. It measures the surface, which is precisely the part a synonymiser is built to move.
The write-up, with both pools assessed and the file that replicates them: synonymizing content google
Run the deletion pass before the publishing decision rather than after, because it resolves a question the dashboard never will: what does a reader find on the second page that they did not see on the first. If the answer is a different arrangement of the same sentence, more variation will not fix it, and the number that says otherwise is measuring the wrong surface.