In the meantime, Google seems to have developed a pretty good ranking system that is difficult to game.
In practice I understand this happens via citation-swapping (similar to link swapping, or paid links in blogs) and poor-quality journals accepting articles for a fee, or without review (much like paid content, or content farms) and papers that cite other articles just for the increase in rankings (similar to link farms) so the analogy to SEO (in its various hats) seems to fit.
This would suggest that the only way to fix the 'broken' citation ranking system is the same as Google, and bolt on empirically determined heuristics above the pure mathematical model of PageRank, and black-list or penalise certain journals or types of citation?
The impact of Google doing this is, in financial terms, probably much larger than if the same type of approach would be applied in the academic situation. So if Google is allowed to do this, why can't we allow the same approach for research? Apparently, the system works quite well.
Compare this to the situation in rating of academic research, where the papers are rated by the community of authors itself and the ranking is essentially a weighted counting of references. Of course it leads to lots of self-serving spam.
If the idea of independent raters (and possibly machine learning on top of it) could be implemented for academic papers as well, that would be a big improvement, I think. Academia has got a lot to learn from search engines.
I wouldn't call prioritizing quantity over quality gaming the ranking system, it is merely playing by its rules. I would call gaming it if there was some cheat (like you cite me and I cite you even if really we shouldn't), which may happen but I believe is rare.