robcat2075 wrote: ↑Tue Apr 01, 2025 9:08 am
If I read their conclusions right, as an occupation declines, younger people tend not to enter it and older people hang on to it, ...
Well, this is where description and categorization can make differences in the meaning of what you say and the meaning of statistics derived from observations using those descriptions/categorizations. If the occupation is "horse team driver", then yes younger people tend not to enter it. If the occupation is "delivery driver" than young people do tend to enter it -- but driving trucks rather than horses.
causing the average age to the occupation's worker set to skew older.
Yes, if the occupation is "horse team driver", but not if the occupation is "delivery driver," and definitely not if the occupation is "motor truck delivery driver."
When some new workers ARE needed it becomes more expensive to get new people to jump in.
Yeah ... see? When some new workers AT WHAT JOB? it will be hard to get "new workers" to jump into the "horse driving" job (but how realistic is it to imagine that the number of those "needed" would be significant), but not the "motor truck driving" job. And then, if you use a broader category to generate your observations and statistics, like "delivery driver" (encompassing both horse and motor truck driver) you'll get even different statistics. Add to that the effect of "re-training" early or mid-career workers (or even late-career workers who may be willing) in the "delivery driver job" (which now has shifted to be about the same population as the "motor truck delivery driver" job, and you get even more complication in your analysis.
I wonder how that will play out in the current situation where the first move of employers in tightening economics has been to unload the older workers first and keep the cheaper younger ones.
If it's the tech area that's under discussion, I think it's a myth that you'll need a lot of the "old workers" to maintain limping and antiquated systems. People think that converting those old implementations and services will be a mind-boggling task of complexity. But -- for several different reasons -- it won't. People think of all those "millions of lines of code that have to be converted" the millions of data base tables that need conversion, and of "programmers" toiling to change that code, or change the databases -- their fingers getting bloodied on the keyboards as they work long overtime hours to replace these massive systems, while others hold back the darkness by actively supporting the antiquated ones. It ain't gonna be that way. It ain't that way now. And a secondary market will develop to aid it as well. Again, the major stumbling blocks in transitions like this (whether they're technological or business process) are organizational -- making the decisions and achieving the agreements to move forward. I've seen this happen over a couple of decades both in the software industry and in the (highly regulated) pharmaceutical industry. I don't mean to belittle or demphasize the amount of work and time that will be involved. But it's not the impossibility that most people think it is.
I doubt anyone in 1900 was aspiring to be a teamster ...
I don't. That's pre-WWI, in which horses were still used in substantial numbers on the battlefield. Even in the 1920s in the US there was still widespread use of horses and mules in farming. There are still people living within a few miles of me who remember plowing with mules. But that was really at the end of the horse-drawn era. Watch this season of that Paramount+ "1923" series and you'll get a pretty accurate picture of the use of motor cars and trucks alongside horses and mules in large sections of the US.
Also interesting, as the paper looked at some c. 1900 declining female careers, was that skilled female jobs (dress and hat makers) seemed to pay way more than the skilled jobs driving horses.
Pretty much any grunt with enough stubbornness and muscles can learn to drive a horse and wagon. Dress making and hat making were arts.