"Paper count" is about as reliable a metric as "lines of code". Publish or die is a toxic mentality in academia and you are certainly not the first to have observed this, sadly.
And while publications do help you, say in getting hired and promotions, your publications are dug into pretty deeply. They don't want to be tricked into hiring someone useless who can crank out fluff but can't win a grant.
By whatever metric you use, it's really about the checklist rather than substance. And the checklists are based on stereotypes, and get gamed.
Indeed in some ways it's worse. When the money is insufficient, the established researchers get it first. Then everyone else has to increasingly work for established researchers as postdocs and similar positions... helping to yet further boost the advantage of the established researchers. It went from senior researchers versus junior researchers, to senior researchers with a herd of postdocs working for them, versus junior researchers.
At least if it was based on publications, everyone gets co-authorship and in fact the first author counts most. So the postdoc and the PI gain the same new items on their CV's for their collaboration. For grants, credit goes entirely to the PI.
In software, we have "source code distributions", such as Debian, Fedora, Gentoo, Arch, Red Hat, SUSE, etc. They are collections of mostly a same free software, with minor differences, but with different policies and purpose. Some are conservative collections of proven software, others are bleeding edge, etc.
IMHO, someone should start to collect papers, which are worth reading, and keep this collection up to date, with fixes to papers (AKA as patches in software), with one paper per topic, with ready to use math models and simulations, with in software tests for models, etc.
I am interested in Amyotrophic Lateral Disease and I blog about research done on ALS [0].
However there are 15,000 scientific papers published each year on this topic, on average only 20 to 30 articles per year are worth spending the time to read them (one every 500) and a milestone appears only every 3/4 years (TDP-43 in 2006, C9orf72 in 2011, etc).
After 100 years there is still no clue about ALS etiology. Scientists have strong but widely different opinions such as for some it starts in the brain motor area, for other it starts at the peripheral nerve junction with muscles, for other (new trend) it starts in the gut.
And scientists happily pursue hypothesis that their colleagues are supposed to have disproved. Sometimes the same lab (I have one in mind which is perhaps the best known in ALS research) publishes articles contradicting its previous research without discussing the issue.
How to rationally blog about this domain, how to make collections that are worth reading?
Every year there are 15 gazillion modules published to NPM, on average only 20-30 are worth spending the time to read, and only a handful milestones worth including in said distributions.
After 100 years there is still no clue weather microservices or monoliths are the correct hypothesis and some times the same lab publish articles contradicting previous research.
IMHO, something similar can be applied to science. Leaders can chose a general direction of a collection of papers, while maintainers will work on small areas, keeping them consistent and up to date with new research.
For example:
- LIGO/VIRGO discovery of gravitational waves means that the speed of light in vacuum is not constant. It's constant in "steady" vacuum only.
- Discovery of Higgs boson means that vacuum is not an empty space, because Higgs field is present everywhere.
These recent discoveries significantly changes the field of science, so a bunch of classic paper must be updated or discarded in favor of new ones.
This still describes a lot of software engineering.