Legitimate decreases need to be considered, too.

I would think of it not so much as a gold rush as picking the low-hanging fruit. For example in the areas of mathematics that interest me, the well-known ideas need little more than tidying up and, hard for most mathematicians, introducing in simple terms. The less fashionable topics remain poorly represented.

I find it hard to believe that Eternal September has arrived, any more than I can believe that the young have less respect for their elders than they used to, or that policemen are getting younger, or that nobody cooks like my mother used to. I think it is more a case of the old hands having built up knowledge and experience they have forgotten they did not have back in the day. To me, Eternal September protagonists are living evidence of the stick-in-the-mud phenomenon - the ones who dominate Stage 3.

The common pattern across language communities does come as a surprise. But to me it does not suggest Eternal September, rather that the stick-in-the-muds have gone global. I can well believe that the global rollout of tools and policies designed to stifle inexpert enthusiasm is doing just that. Revert rates without context prove nothing: they may be down to young vandals, or old stick-in-the-muds clinging to their territory, or arguments over translating from the original English, who can say without the context. Perhaps many language communities are not so much in Stage 3 as being sucked into it prematurely by the biggest and most influential community - a community that has already got there.

Steelpillow 16:17, 12 March 2011 (UTC)

In addition to the "gold rush" and "low hanging fruit" principles, I would like to add that a major problem on Wikipedia is that articles on small self-contained topics are much more well-developed than core encyclopedic content. While almost all basic topics have articles with sources, many of them are still in a miserable state, because editors need to bring together a wide range of sources and expertise to improve them: it is much easier to work on quirky topics, where there are only a few reliable sources, so that selection bias is not a problem and relevant knowledge can be acquired easily.