You need to learn what to avoid: http://shape-of-code.coding-guidelines.com/2016/06/10/finding-the-gold-nugget-papers-in-software-engineering-research/
Andrew Gelman's blog has lots of what you are after: https://statmodeling.stat.columbia.edu/
If you are into data analysis and software engineering there is my book Evidence-based software engineering.
pdf+data+code here: http://knosof.co.uk/ESEUR/
I wish you lots of luck. Don't go so far north that day trippers from the south cannot drop by :-)
You are one of the few people with the discipline to record what they do and create todo lists. I could not keep this up for a week. Do you try to estimate the time it will take to complete a task?
Have you done any global analysis of your data? I analyse software engineering data and am always on the lookout for more data. I offer a free analysis, provided the data can be made public (in anonymous form). Here is one I did earlier:
More examples of the difficulty of predicting the future using fitted regression models:
Take some interesting ideas that allow larger structures to be built up, run an awful lot of computer simulations, and then have somebody who knows a huge amount about physics look for those outputs that match how parts of the universe have been previously modeled (with some success).
Where are the predictions? There are no predictions about basic stuff we know, like the electron orbitals of a Hydrogen atom, let alone predictions about stuff we don't know.
This work looks interesting, and Wolfram is a great story teller. I hope something comes of it, but at the moment it is pure arm waving of just-so stories found in the output from a few computer runs.
The ACM is offering free download of their articles: https://dl.acm.org/
“Who we are and how we got here” by David Reich (a genetics professor who is a big name in the field), is the story of the various migrations and interbreeding of ‘human-like’ and human peoples over the last 50,000 years (with some references going as far back as 300,000 years).