Is this something like "list starts with type A, and that will tell you if the next node is type A or B"?
Is there a way to stuff those bits in with the node somehow so you always know the type you expect back?
https://news.ycombinator.com/item?id=23093789
The political solution is to give an estimate assuming nothing goes wrong, and then when things go wrong blame those things.
This lets everybody from you up the chain look good while not changing anything.
A friend cashed out mid 40s but is the kind of person who doesn't stop. Did real estate, baking, landscape, had a kid, seems up for anything and quite content.
A another is wealthy enough to stop working at anytime but doesn't want to retire.
I slowly slid into retirement in mid 30s. Started out great. I sometimes work part-time and program for fun a bit. But when kid #2 and #3 came it was very difficult for me. Being retired was the saving grace that made it work at all. Now things are slowly getting better.
For me a normal day is 4-5 hours for kids, 1-2 hours walking/biking, 2-3 hours reading/programming/working. Then there is always something (doc appt, car repair, house stuff) in there somewhere.
Best part is the flexibility to do things during weekdays. Meet with friend/family for lunch, random escape room, errands.
Worst part is not having the camaraderie of good coworkers working together. I had one job that was great in that respect and gave me lasting friends. Other jobs not at all.
Financial freedom is amazing but everyone handles it differently. Best advice I have is if retirement is an option see if you can try it for 3-12 months.
Graph of Federal Government receipts as percentage of GDP.
Does this show that gutting the IRS has resulted in lower tax revenue?
Enforcement involves substantial interpretations that reasonable people in and out of the IRS can disagree on.
This is not an argument for more or less enforcement, but I've found people usually neglect this aspect.
This is the first I've heard this kind of statistic. Does anybody have a reference for where this came from?
https://www.hudsonrivertrading.com/careers/
Looks like c++, python, and linux sysadmin stuff.
Example: Health Care
Visible goal: Improve Health
Hidden goal: Show how much we care ("kiss the booboo")
This explains why much of health care is devoted to high-cost high-visibility interventions (like bypass surgery) and much less to lifestyle interventions (like diet/exercise).
It also explains why many obvious changes that would improve the stated goal keep failing to be adopted - they hamper the hidden goals.
Software example: Why do people keep estimating development task size assuming nothing goes wrong? And why do their managers not hold them responsible for continually slipping the schedules?
Visible goal: Accurate estimates
Hidden goal: Brag about how fast we are
If accurate estimates were the only goal, then when schedules slip there would be a strong feedback loop to improve future estimates. My experience has been the opposite - the slip is blamed on something "no one could have foreseen" and everybody keeps estimating as before.
To be clear, it's always a mix of the visible and hidden motives. Much of health care is actually about improving health. But acknowledging the hidden motives is vital to understanding how much of society works.
My company is looking for someone we can send a personalized pdf to and they print, stuff, and mail it. In volume. A quick search turns up:http://www.postalmethods.comhttp://click2mail.comCan anyone recommend either these or others that they've used?
Ended up ripping all the placeholder stuff out.
A later paper by them backs off: http://www.eis.mdx.ac.uk/research/PhDArea/saeed/paper3.pdf
Abstract: Learning to program is notoriously difficult. Substantial failure rates plague introductory programming courses the world over, and have increased rather than decreased over the years. Despite a great deal of research into teaching methods and student responses, there have been to date no strong predictors of success in learning to program. Two years ago we appeared to have discovered an exciting and enigmatic new predictor of success in a first programming course. We now report that after six experiments, involving more than 500 students at six institutions in three countries, the predictive effect of our test has failed to live up to that early promise. We discuss the strength of the effects that have been observed and the reasons for some apparent failures of prediction.