There are some incentives to make work reproducible. If you publish a method implemented in software, then making that software easy to use, well documented, with example data and respond to questions/issues etc it greatly enhances the chance other people will use it and cite it. Things have been getting much better in the last 5 years.
Preprints also help - I saw a preprint the other day where people complained on twitter there was no methods section and no code. The authors responded. They realise that potential reviewers may be the ones making these comments or at least see the comments. This talks to your point about not treating a paper as a single point in time, but an ongoing process.
I think things are improving. I am now seeing papers publish Jupyter notebooks in python or R scripts to reproduce all the diagrams and analyses, along with curated data that just plugs in. In general this actually works (although sometimes crucial bits of data are missing, and unlike an error in the paper, these are not necessarily fixed).