Thread:Talk:Article feedback/Suggestion: do not ask feedback from any of article

As reported before, the system will currently ask even the sole author of an article for feedback on that article. While a fix for that behaviour was already requested (Bug 29212), I'd like to push the concept further.

I find it odd to ask a co-author what he thinks of an article to which he has contributed (no matter how long ago, or how significantly). On controversial topics, one can only imagine the result (goodbye edit wars, hello ratings wars!). The irony is that “experts” on the topic (highly prized for ratings, apparently) are more likely to themselves be editors of said topic and have a conflict of interest.

An encyclopedia, ultimately, is useful to readers who are relatively new to the topic about which they are reading; it's not a super-notebook or database for scholars. The pool of casual readers, with or without some knowledge of the topic, is hopefully large enough to get meaningful ratings; if it isn't, the article probably wasn't suitable for inclusion in an encyclopedia. In short, excluding all co-authors from rating the article is, I believe, not much of a loss.

Note that I am not arguing in favour of some unattainable system aiming to curtail abuse: sockpuppet and meatpuppet masters would always be able to game the system. All I am suggesting is that we simply refrain from actively encouraging co-authors to rate their own articles.

I can see a few obvious drawbacks with this suggestion: (1) performance hit (searching for the name of the logged-in user into the list of contributors). (2) does not work until the reader has signed in (but is ArticleFeedback presented to those anyway?). (3) anonymous (IP) authors can't be identified for sure, but that's not a problem: we can still exclude the IP at large, since we're just collecting statistical feedback.

In the end, one could at least prepend a cautionary note to the article feedback form, advising users to not rate articles to which they have contributed (or are about to contribute). And the analysis backend could, without any performance hit on readers, filter out ratings submitted by co-authors (assuming that their user name remains associated to the rating, which may or not be a privacy concern).