> We regularly close issues that are 1+ year old on Jupyter/IPython or rescope the issue to be actionable for contribution.

Sorry if me doing that on IPython/Jupyter recently have put you (willingc) in a bad position in here, sincere apologies, you are doing a great job.
On the Jupyter/IPython repositories we find that too many open issues and/or patch proposals open tend to repel contributors away. So we try to actively clean things up, especially the ones that are old and inactive. It's true that project might have different policies though. 

I, personally, would prefer some of my patch/issues to be closed with a "Sorry, we don't have time to review that and that's going to be controversial anyway, though we appreciate you doing the effort" than leave them in limbo with no responses. 

It happen of course that committers overzealously close issue, of course – we are human after all and make mistakes, whether we have years of experience, or  a new contributor who does not know the protocol.  It is always a good time to show the example, and show how we could have improved the process.I don't think that making a mistake should be seen as dramatic as it's often communicated. After all, we have revision control, and we can reopen right ?

For example, I think that recently we [IPython/Jupyter] did a better job at reopening and explaining what could have been done better – and actually do it – instead of what was not done. But most of the time the closing of languishing issue was the right choice, and the cost/benefit, despite the false positive was worth it.

I also think the closing an issue [with or without patch], make the author react if they really do care, often more than that if you just ask for a status update. This author, in general, is often more aware of potential new issues that supersede the closed one and thus can link to it.

Again, I know that working on multiple projects can be hard and that practices that differ between project can also be hard to follow, and my recent spring-cleaning might have biased your practices here. Thanks for your hard work both on IPython/Jupyter, here and at on the PSF board, and sorry if it put you into trouble.