Does A Uniqueness Score Prove Anything About A Generated Page

Does a uniqueness score prove anything about a generated page


The question arrives every time a spam update lands, and it arrives in the same shape: someone has a collection of generated pages, a checker that reports them as highly distinct from one another, and a feeling that the figure is not answering the question they really have. They are correct to be wary, and the reason is easier to demonstrate than to argue about, because both parts of it can be measured on the same set of pages in around a second.


I generate location pages for one service, one page per town, from a skeleton with plenty of synonym slots. My checker says the pages barely overlap, which everyone tells me is the goal. 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 trust, my score or their page?


Both, because they are not measuring the same thing. The policy wording is about what a batch of pages is for and how little it adds for the reader; the method is clearly not the violation, and the same sentence says so whether a individual or a system did the writing. A similarity score, meanwhile, measures variation density over short runs of words. A pool can push that score as far as it goes and still say 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 takes one pass. Replace every value that originated from data, the town name included, with a substitute, and check the pool again. If what remains is many pages that are still unique, the template produced them and the reader receives one page every time. If what remains collapses to a single page repeated, the data was carrying the difference, and the pages are worth as much as the data behind them is. That second part the test cannot resolve for you, and no measurement will.



The write-up, with both pools assessed and the file that reproduces them: google spam policy ai content



Run the deletion pass before the publishing decision rather than after, because it resolves a question the dashboard never will: what does a reader get on the second page that they did not see on the first. If the answer is a different configuration of the same sentence, more variation will not fix it, and the number that claims otherwise is measuring the wrong surface.